Microrna assay for detection and management of pancreatic cancer precursors

ABSTRACT

The current invention pertains to miRNAs that are differentially expressed in samples of an individual having pancreatic cancer, or having a high risk of developing pancreatic cancer, as compared to the corresponding sample of an individual not having pancreatic cancer, or having low risk of developing pancreatic cancer, respectively. In certain embodiments, the miRNAs are differentially expressed in a tissue sample or blood plasma sample of an individual having a pancreatic lesion and having a high risk of developing pancreatic cancer as compared to the corresponding tissue sample or blood sample of an individual having the pancreatic lesion and having no risk or low risk of developing pancreatic cancer. These differentially expressed miRNAs can be used as biomarkers for diagnosis, treatment, and/or prevention of pancreatic cancer, particularly, in a subject having a pancreatic lesion. Microarray containing miRNAs indicative of the presence of pancreatic cancer, or having a high risk of pancreatic cancer development, particularly, in a subject having a pancreatic lesion, and methods of use of the microarrays are also provided.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. application Ser. No.17/233,855, filed Apr. 19, 2021, which is a continuation of U.S.application Ser. No. 16/362,623, filed Mar. 23, 2019, which is acontinuation of U.S. application Ser. No. 15/300,808, filed Sep. 30,2016, now U.S. Pat. No. 10,240,208, which is the National Stage ofInternational Application Number PCT/US2015/023702, filed Mar. 31, 2015,which claims the benefit of U.S. Provisional Application Ser. No.61/973,068, filed Mar. 31, 2014, each of which is hereby incorporated byreference herein in its entirety, including any figures, tables, nucleicacid sequences, amino acid sequences, or drawings.

GOVERNMENT SUPPORT

This invention was made with government support under grant numbersCA076292 and CA129227 awarded by the National Institutes of Health. Thegovernment has certain rights in the invention.

SEQUENCE LISTING

The Sequence Listing for this application is labeled “2SN9055.TXT” whichwas created on Dec. 16, 2021 and is 13.5 KB. The entire contents of thesequence listing is incorporated herein by reference in its entirety.

BACKGROUND OF THE INVENTION

Intraductal papillary mucinous neoplasms (IPMN) areincidentally-detected pancreatic cysts that are challenging to managedue to the inability to predict which cysts can be safely monitored,which are likely to progress to invasive pancreatic cancer, and whichmay have an associated invasive component. Differentiating betweenhigh-risk and low-risk intraductal papillary mucinous neoplasms (IPMNs)of the pancreas is a significant clinical problem.

Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause ofcancer mortality in the United States, claiming the lives of nearly40,000 individuals each year. Surgical resection offers the best chancefor improved survival, but 80-85% of cases are unresectable atdiagnosis. These statistics underscore the urgent need to developstrategies to detect PDAC at an early, operable stage.

It is established that PDAC does not arise de novo, but instead marksthe end of progression from one of three types of non-invasive precursorlesions arising within exocrine pancreatic ducts: pancreaticintraepithelial neoplasia (PanIN), mucinous cystic neoplasms (MCNs), andintraductal papillary mucinous neoplasms (IPMNs). While PanINs aremicroscopic lesions in ducts <5 mm in diameter, MCNs and IPMNs aremacroscopic mucinous cysts accounting for over half of the estimated150,000 asymptomatic pancreatic cysts detected incidentally in thegeneral population each year due to increased computed tomography andmagnetic resonance imaging. Although improvements in imaging, cytology,and molecular studies have enabled proper classification and managementof some benign non-neoplastic pancreatic cysts, mucinous cysts such asIPMNs are challenging for the patient and clinical team to manage due tothe inability to accurately predict which lesions can be monitored,which are likely to progress to invasion, and which may have anassociated invasive component. Since data highlight a two-decade windowof opportunity for early detection efforts in PDAC, IPMNs representprime targets for the early detection and prevention of progression toinvasive, fatal disease.

IPMNs present within the main pancreatic duct (MD-IPMN), side branchducts (BD-IPMN), or both (mixed-IPMN), and are further classified basedon the degree of dysplasia which ranges from adenoma (low-gradedysplasia, LG) and borderline (moderate-grade dysplasia, MG) tocarcinoma in situ (high-grade dysplasia, HG) and invasive carcinoma (2)(FIGS. 4A-4D). MD-IPMNs are associated with a higher grade and fastergrowth compared to BD-IPMNs, with the 5-year risk of developing HG orinvasive disease from an adenoma to be ˜63% for MD-IPMNs and 15% forBD-IPMNs. Other predictors of malignant potential include main ductdilation (>5 mm), mural nodules, cyst size (>3 cm), and symptoms such asjaundice and abdominal pain. Consensus guidelines recommend resectionfor surgically-fit patients with MD-IPMNs and careful observation forasymptomatic BD-IPMNs measuring <3 cm in the absence of mural nodules,main-duct dilation, or positive cytology. However, these guidelines donot reliably predict the degree of dysplasia. To date, the only way totreat IPMNs and accurately identify the grade of dysplasia is throughsurgical resection and pathological evaluation, but the risks ofmorbidity (i.e. long-term diabetes) and mortality associated with aWhipple procedure or a distal or total pancreatectomy may outweigh thebenefits, especially for patients with LG disease. Alternatively, takinga ‘watch and wait’ approach could lead to a missed opportunity to cure apatient harboring occult invasive disease.

Although many DNA-, RNA- and protein-based markers are underinvestigation as markers of early pancreatic neoplasia, most requirefurther validation. MicroRNAs (miRNAs) are small non-coding RNAs thatregulate nearly one-third of all protein-coding genes by binding to the3′ untranslated region of the targeted messenger RNA (mRNA). Theirability to regulate (and serve as) tumor suppressors and oncogenes,their remarkable stability in formalin-fixed paraffin-embedded (FFPE)tissue and biofluids, and their dysregulated expression in PDACscompared to normal pancreas tissue makes miRNAs excellent candidatebiomarkers of early progression to pancreatic malignancy. Indeed, earlystudies of small numbers of miRNAs supported a role for altered miRNAexpression in PanINs and IPMNs. Since over 1,000 miRNAs exist (21), wesought to conduct the first genome-wide investigation of miRNAs to befollowed by both a replication and a functional follow-up phase (FIG.5), with the goal of discovering miRNAs that accurately differentiatehigh-risk (HG and invasive) IPMNs that may require resection fromlow-risk (LG and MG) IPMNs that can be monitored.

BRIEF SUMMARY OF THE INVENTION

Certain embodiments of the current invention provide miRNAs that aredifferentially expressed in a sample of an individual having pancreaticcancer, or having a high risk of developing pancreatic cancer, ascompared to the corresponding sample of an individual not havingpancreatic cancer, or having low risk of developing pancreatic cancer.In one embodiment, each of the individuals having high risk ofdeveloping pancreatic cancer and the individual having low risk ofdeveloping pancreatic cancer have a non-invasive precursor lesionarising within exocrine pancreatic ducts (hereinafter, pancreaticlesion), for example, pancreatic intraepithelial neoplasia (PanIN),mucinous cystic neoplasms (MCNs), and intraductal papillary mucinousneoplasms (IPMNs). The miRNAs that are differentially expressed in asample of an individual having pancreatic cancer, or having a high riskof developing pancreatic cancer, can be used as biomarkers fordiagnosis, treatment, and/or prevention of pancreatic cancer.

The miRNAs identified herein can be used to identify subjects that havepancreatic cancer to distinguish them from subjects that do not havepancreatic cancer, or to identify subjects having a higher risk ofdeveloping pancreatic cancer to distinguish them from subjects that havea lower risk of developing pancreatic cancer, or to identify subjectshaving a pancreatic cancer precursor (such as intraductal papillarymucinous neoplasm (IPMN)) versus a non-IPMN, or to identify subjectsthat have a malignant IPMN versus a benign IPMN. Thus, these miRNAs canbe used as an adjunctive tool to guide decisions regarding monitoring,treatment, and management of pancreatic cancer.

Certain other embodiments of the current invention provide microarraysof oligonucleotides corresponding to the miRNAs that are differentiallyexpressed in a sample of an individual having pancreatic cancer, orhaving a high risk of developing pancreatic cancer, for example, whenthe individual has a pancreatic lesion. In one embodiment, the sample isa cell sample, such as a blood cell, and accordingly, the currentinvention also provides a blood-based minimally-invasive miRNA assaythat can be used in an individual having a pancreatic lesion to assesshistologic severity. In another embodiment, the miRNAs indicative ofpancreatic cancer are detected in cell-free samples from a subject, forexample, body fluid samples from a subject, such as whole blood, plasma,serum, urine, or pancreatic cyst fluid. As such, the current inventionprovides miRNAs that can be used to differentiate between the presenceor absence of pancreatic cancer, high-risk or low-risk pancreaticlesions, for example, IPMNs, that warrant treatment (such as surgicalresection, pancreatoduodenectomy (Whipple procedure), immunotherapy,radition, or chemotherapy) and low-risk pancreatic lesions, for example,IPMNs, that can be monitored. Monitoring and confirmation of thepresence of pancreatic cancer or lesions can be carried out, forexample, by imaging (e.g., endoscopic ultrasound, MM, or CT scan).

BRIEF DESCRIPTION OF THE DRAWINGS

The patent or application file contains at least one drawing executed incolor. Copies of this patent or patent application publication withcolor drawing(s) will be provided by the Patent and Trademark Officeupon request and payment of the necessary fee.

FIGS. 1A and 1B. Laser capture microdissection (LCM) of epithelium fromlow-grade IPMN tissue (FIG. 1A) and high-grade IPMN tissue (FIG. 1B).Left Panel: Hematoxylin (H&E) stained slide (×4). Middle Panel: H&Estained slide before LCM (×4), with the red area representing cells ofinterest marked for capture. Right Panel: Cap showing adherent cells.

FIGS. 2A and 2B. Heatmap and unsupervised hierarchical clustering oflow-risk (adenoma) and high-risk (carcinoma-in-situ) IPMN samplesaccording to the expression of the most differentially expressed miRNAs.FIG. 2A: The heatmap is supervised, and is ordered by the type of IPMN,and shows the expression for the 25 most deregulated miRNAs. FIG. 2B:Unsupervised hierarchical clustering for the 6 most differentiallyexpressed miRNAs. Expression values for the miRNAs are represented in amatrix format, with columns representing samples and rows representingmiRNAs. Low expression values are colored green, and high expressionvalues are colored red. Colored bars indicate the range of normalizedlog₂-based signals.

FIG. 3. Receiver operating characteristic (ROC) curve analysis usingmiRNA expression to discriminate high-risk from low-risk IPMN samples.Using a logistic regression model built on data from the discoverydataset, a miRNA signature consisting of miR-99b, miR-130a, andmir-342-3p yielded an area underneath the curve (AUC) value of 0.74 (95%CI: 0.51-0.97) in differentiating between 13 high-risk and 8 low-riskIPMNs in the replication phase.

FIGS. 4A-4D. Representative histologic images of IPMNs with low-grade(FIG. 4A), moderate-grade (FIG. 4B), and high-grade dysplasia (FIG. 4C)and invasive (FIG. 4D) carcinoma. The region enclosed by the black linerepresents the area isolated by LCM. Reference bar=50 micrometers (mm).

FIG. 5. Schema illustrating the three study phases. In the discoveryphase, genome-wide miRNA expression profiling of formalin-fixedparaffin-embedded (FFPE) tissue from 28 IPMNs was conducted. This wasfollowed by a replication phase in which the six most degregulatedmiRNAs from the discovery phase (miR-100, miR-99b, miR-99a, miR-342-3p,miR-126, and miR-130a) were evaluated in an independent set of 21 IPMNs,while accounting for pertinent clinical and pathologic variables. In thefinal phase, a two-pronged approach was used to follow up findings: a)bioinformatics analyses were conducted to identify genes and pathwaysregulated by the candidate miRNAs and b) analysis was performed forcandidate genes believed to be regulated by the identified miRNAs usingexisting microarray data for 23 IPMNs.

FIGS. 6A and 6B. Box plots of candidate miRNA expression in IPMN tissueby real-time PCR. FIG. 6A: Discovery phase; FIG. 6B: Replication phase.On each boxplot, the central mark is the median, and the edges of thebox are the 25th and 75th percentiles. The whiskers extend to the mostextreme data points within 1.5 of the interquartile range above the75^(th) or below the 25^(th) percentiles. Data points beyond thewhiskers, displayed using “o”, are potential outliers.

FIGS. 7A and 7B. Receiver operating characteristic (ROC) curve analysisusing miRNA expression to discriminate high-risk from low-risk IPMNs inthe discovery (FIG. 7A) and replication (FIG. 7B) phase.

FIG. 8. Network of genes regulated by candidate miRNAs (miR-100,miR-99a, miR-99b, miR-342-3p, miR-126, and miR-130a) that were found tobe differentially expressed between high- and low-risk IPMNs.

FIG. 9. Box plots of miRNA expression in IPMN tissue by real-time PCR.The expression level of the top-ranked miRNAs was down-regulated inhigh-grade compared to low-grade IPMN tissue.

FIGS. 10A-10C. A 30-miRNA signature discriminates IPMN Cases (N=42) fromHealthy Controls (N=24). FIG. 10A: Percentage of variation explained inthe first 5 principal components using the 30 miRNA signature. FIG. 10B:Association of the 30-miRNA signature with case-control status. Boxplots were used to display the distribution of the IPMN-risk malignancyscore within each group. Two-sample t-tests were used to determineassociations between the continuous PC1 score and case-control status.FIG. 10C: Receiver operating characteristic (ROC) curve analysis usingmiRNA expression to discriminate IPMN cases from healthy controls. The30-miRNA signature PC1 yielded an area underneath the curve (AUC) valueof 74.4 (95% CI: 62.3-86.5) in differentiating between groups.

FIGS. 11A-11D. Heatmap of the 30-miRNA signature in IPMN cases andnon-diseased controls.

FIGS. 12A-12B. miR-145-5p expression differentiates between cases andnon-diseased controls. FIG. 12A: Box plot reveals miR-145-5p expressionis higher in cases versus controls. FIG. 12B: ROC analysis reveals thatmiR-145-5p expression can differentiate between groups with an AUC=79.3(95% CI: 68.3-90.3).

FIGS. 13A-13D. Heatmap of the KEGG pathways enriched for genes targetedby the 30 differentially expressed miRNAs.

FIGS. 14A-14C. FIG. 14A: Percentage of variation explained in the 5principal components using the 5 miRNA signature. FIG. 14B: Associationof the 5-miRNA signature with IPMN malignancy status. Box plots wereused to display the distribution of the IPMN-risk malignancy scorewithin each group. Two-sample t-tests were used to determineassociations between the continuous PC1 score and IPMN malignancystatus. FIG. 14C: ROC curve analysis of the 5-miRNA signature yielded anAUC of 73.2 (95% CI: 57.6-88.9) in differentiating between groups.

BRIEF DESCRIPTION OF THE SEQUENCES SEQ SEQ miRNA ID NO: Pre-miRNA ID NO:Mature miRNA hsa-miR-  1 CCUGUUGCCACAAACCCGUAGAUCCGAA 24 AACCCGUAGAUCCGA100-5p CUUGUGGUAUUAGUCCGCACAAGCUUG ACUUGUG UAUCUAUAGGUAUGUGUCUGUUAGGhsa-miR-  2 CCUGUUGCCACAAACCCGUAGAUCCGAA 25 CAAGCUUGUAUCUA 100-3pCUUGUGGUAUUAGUCCGCACAAGCUUG UAGGUAUG UAUCUAUAGGUAUGUGUCUGUUAGG hsa-miR- 3 GGCACCCACCCGUAGAACCGACCUUGCG 26 CACCCGUAGAACCGA 99b-5pGGGCCUUCGCCGCACACAAGCUCGUGUC CCUUGCG UGUGGGUCCGUGUC hsa-miR-  4GGCACCCACCCGUAGAACCGACCUUGCG 27 CAAGCUCGUGUCUG 99b-3pGGGCCUUCGCCGCACACAAGCUCGUGUC UGGGUCCG UGUGGGUCCGUGUC hsa-miR-  5CCCAUUGGCAUAAACCCGUAGAUCCGAU 28 AACCCGUAGAUCCGA 99a-5pCUUGUGGUGAAGUGGACCGCACAAGCU UCUUGUG CGCUUCUAUGGGUCUGUGUCAGUGUG hsa-miR- 6 CCCAUUGGCAUAAACCCGUAGAUCCGAU 29 CAAGCUCGCUUCUA 99a-5pCUUGUGGUGAAGUGGACCGCACAAGCU UGGGUCUG CGCUUCUAUGGGUCUGUGUCAGUGUG hsa-miR- 7 GAAACUGGGCUCAAGGUGAGGGGUGCU 30 UCUCACACAGAAAUC 342-3pAUCUGUGAUUGAGGGACAUGGUUAAUG GCACCCGU GAAUUGUCUCACACAGAAAUCGCACCCGUCACCUUGGCCUACUUA hsa-miR-  8 CGCUGGCGACGGGACAUUAUUACUUUU 31CAUUAUUACUUUUG 126-5p GGUACGCGCUGUGACACUUCAAACUCG GUACGCGUACCGUGAGUAAUAAUGCGCCGUCCACG GCA hsa-miR-  9 CGCUGGCGACGGGACAUUAUUACUUUU32 UCGUACCGUGAGUA 126-3p GGUACGCGCUGUGACACUUCAAACUCG AUAAUGCGUACCGUGAGUAAUAAUGCGCCGUCCACG GCA hsa-miR- 10 UGCUGCUGGCCAGAGCUCUUUUCACAU33 UUCACAUUGUGCUA 130a-5p UGUGCUACUGUCUGCACCUGUCACUAG CUGUCUGCCAGUGCAAUGUUAAAAGGGCAUUGGCC GUGUAGUG hsa-miR- 11UGCUGCUGGCCAGAGCUCUUUUCACAU 34 CAGUGCAAUGUUAA 130a-3pUGUGCUACUGUCUGCACCUGUCACUAG AAGGGCAU CAGUGCAAUGUUAAAAGGGCAUUGGCCGUGUAGUG hsa-miR- 12 GGCAGUGCUCUACUCAAAAAGCUGUCA 35 UACUCAAAAAGCUG888-5p GUCACUUAGAUUACAUGUGACUGACAC UCAGUCA CUCUUUGGGUGAAGGAAGGCUCAhsa-miR- 13 GGCAGUGCUCUACUCAAAAAGCUGUCA 36 GACUGACACCUCUU 888-3pGUCACUUAGAUUACAUGUGACUGACAC UGGGUGAA CUCUUUGGGUGAAGGAAGGCUCA hsa-let-7c-14 GCAUCCGGGUUGAGGUAGUAGGUUGUA 37 UGAGGUAGUAGGUU 5pUGGUUUAGAGUUACACCCUGGGAGUUA GUAUGGUU ACUGUACAACCUUCUAGCUUUCCUUGG AGChsa-let-7c- 15 GCAUCCGGGUUGAGGUAGUAGGUUGUA 38 CUGUACAACCUUCUA 3pUGGUUUAGAGUUACACCCUGGGAGUUA GCUUUCC ACUGUACAACCUUCUAGCUUUCCUUGG AGChsa-miR- 16 CUCCCCAUGGCCCUGUCUCCCAACCCUU 39 UCUCCCAACCCUUGU 150-5pGUACCAGUGCUGGGCUCAGACCCUGGU ACCAGUG ACAGGCCUGGGGGACAGGGACCUGGGG AChsa-miR- 17 CUCCCCAUGGCCCUGUCUCCCAACCCUU 40 CUGGUACAGGCCUG 150-3pGUACCAGUGCUGGGCUCAGACCCUGGU GGGGACAG ACAGGCCUGGGGGACAGGGACCUGGGG AChsa-miR- 18 AGGACCCUUCCAGAGGGCCCCCCCUCAA 41 AGGGCCCCCCCUCAA 296-5pUCCUGUUGUGCCUAAUUCAGAGGGUUG UCCUGU GGUGGAGGCUCUCCUGAAGGGCUCU hsa-miR- 19AGGACCCUUCCAGAGGGCCCCCCCUCAA 42 GAGGGUUGGGUGGA 296-3pUCCUGUUGUGCCUAAUUCAGAGGGUUG GGCUCUCC GGUGGAGGCUCUCCUGAAGGGCUCU hsa-miR-20 GCCAACCCAGUGUUCAGACUACCUGUUC 43 CCCAGUGUUCAGAC 199a-5pAGGAGGCUCUCAAUGUGUACAGUAGUC UACCUGUUC UGCACAUUGGUUAGGC hsa-miR- 21GCCAACCCAGUGUUCAGACUACCUGUUC 44 ACAGUAGUCUGCAC 199a-3pAGGAGGCUCUCAAUGUGUACAGUAGUC AUUGGUUA UGCACAUUGGUUAGGC hsa-miR- 22CCACCACUUAAACGUGGAUGUACUUGCU 45 ACUUAAACGUGGAU 302a-5pUUGAAACUAAAGAAGUAAGUGCUUCCA GUACUUGCU UGUUUUGGUGAUGG hsa-miR- 23CCACCACUUAAACGUGGAUGUACUUGCU 46 UAAGUGCUUCCAUG 302a-5pUUGAAACUAAAGAAGUAAGUGCUUCCA UUUUGGUGA UGUUUUGGUGAUGG SEQ ID NO. miRNAAccession Target Sequence 47 hsa-let-7d-5p MIMAT0000065AGAGGUAGUAGGUUGCAUAGUU 48 hsa-let-7f-5p MIMAT0000067UGAGGUAGUAGAUUGUAUAGUU 49 hsa-let-7g-5p MIMAT0000414UGAGGUAGUAGUUUGUACAGUU 50 hsa-let-7i-5p MIMAT0000415UGAGGUAGUAGUUUGUGCUGUU 51 hsa-miR-15b-5p MIMAT0000417UAGCAGCACAUCAUGGUUUACA 52 hsa-miR-20a-5p*² MIMAT000075UAAAGUGCUUAUAGUGCAGGUAG 53 hsa-miR-20b-5p*² MIMAT0001413CAAAGUGCUCAUAGUGCAGGUAG 54 hsa-miR-22-3p MIMAT0000077AAGCUGCCAGUUGAAGAACUGU 55 hsa-miR-23a-3p MIMAT0000078AUCACAUUGCCAGGGAUUUCC 56 hsa-miR-24-3p MIMAT0000080UGGCUCAGUUCAGCAGGAACAG 57 hsa-miR-26a-5p MIMAT0000082UUCAAGUAAUCCAGGAUAGGCU 58 hsa-miR-27a-3p MIMAT0000084UUCACAGUGGCUAAGUUCCGC 59 hsa-miR-29c-3p MIMAT0000681UAGCACCAUUUGAAAUCGGUUA 60 hsa-miR-33a-5p MIMAT0000091GUGCAUUGUAGUUGCAUUGCA 61 hsa-miR-98 MIMAT0000096 UGAGGUAGUAAGUUGUAUUGUU62 hsa-miR-107 MIMAT0000104 AGCAGCAUUGUACAGGGCUAUCA 63 hsa-miR-142-3pMIMAT0O00434 UGUAGUGUUUCCUACUUUAUGGA 64 hsa-miR-145-5p MIMAT0000437GUCCAGUUUUCCCAGGAAUCCCU 65 hsa-miR-146a-5p MIMAT0000449UGAGAACUGAAUUCCAUGGGUU 66 hsa-miR-148a-3p MIMAT0000243UCAGUGCACUACAGAACUUUGU 67 hsa-miR-181a-5p MIMAT0000256AACAUUCAACGCUGUCGGUGAGU 68 hsa-miR-191-5p MIMAT0000440CAACGGAAUCCCAAAAGCAGCUG 44 hsa-miR-199a-3p*⁴ MIMAT0000232ACAGUAGUCUGCACAUUGGUUA 69 hsa-miR-200a-3p MIMAT0000682UAACACUGUCUGGUAACGAUGU 70 hsa-miR-335-5p MIMAT0000765UCAAGAGCAAUAACGAAAAAUGU 71 hsa-miR-337-3p MIMAT0000754CUCCUAUAUGAUGCCUUUCUUC 72 hsa-miR-340-5p MIMAT0004692UUAUAAAGCAAUGAGACUGAUU 73 hsa-miR-423-5p MIMAT0004748UGAGGGGCAGAGAGCGAGACUUU 74 hsa-miR-574-3p MIMAT0003239CACGCUCAUGCACACACCCACA 75 hsa-miR-593-3p MIMAT0004802UGUCUCUGCUGGGGUUUCU 76 hsa-miR-1185-5p MIMAT0005798AGAGGAUACCCUUUGUAUGUU 77 hsa-miR-1260b MIMAT0015041 AUCCCACCACUGCCACCAU78 hsa-miR-4454 MIMAT0018976 GGAUCCGAGUCACGGCACCA *miRNA speciesidentified with an asterisk are targeted by a non-unique probe. Allspecies targeted by the same probe share the same number after theasterisk.

DETAILED DESCRIPTION OF THE INVENTION

The term “about” is used in this patent application to describe somequantitative aspects of the invention, for example, length of apolynucleotide in terms of the number of nucleotides or base pairs. Itshould be understood that absolute accuracy is not required with respectto those aspects for the invention to operate. When the term “about” isused to describe a quantitative aspect of the invention the relevantaspect may be varied by ±10%. For example, a miRNA about 20 nucleotideslong means a polynucleotide between 18 to 22 nucleotides long.

The phrase “one or more miRNAs” in the context of detecting the level ofexpression of miRNAs means that the level of at least one of the recitedmiRNAs is measured using an assay effective in measuring miRNAexpression in the sample from the subject. For example, detecting thelevel of expression of one or more mRNAs selected from amongmiR-200a-3p, miR-1185-5p, miR-33a-5p, miR-574-3p, and miR-663bencompasses measuring the level of expression of one, two, three, four,or all five of the recited miRNAs, and may encompass detecting the levelof expression of further unrecited miRNAs or only the recited miRNAs.

The current invention provides miRNAs that are indicative of thepresence of pancreatic cancer, or high risk of developing pancreaticcancer, in a subject, particularly, when the subject has a pancreaticlesion. For the purposes of this invention, a “high risk of developingpancreatic cancer” indicates that the person has an increased risk ofdeveloping pancreatic cancer in the near future compared to anindividual who is free from pancreatic cancer and has low risk ofdeveloping pancreatic cancer in the near future. For the purposes ofthis invention, the term “near future” refers to a duration of about 1month to about 2 years, about 6 months to about 18 months, or about 1year.

The pancreatic cancer may be of any category (e.g., TX, T0, Tis, T1, T2,T3, T4); any category (e.g., NX, N0, N1, M0, M1); any stage (Stage 0(Tis, N0, M0), Stage IA (T1, N0, M0), Stage IIA (T3, N0, M0), Stage IIB(T1-3, N1, M0), Stage III (T4, Any N, M0), Stage IV (Any T, Any N, M1));resectable; locally advanced (unresectable); or metastatic.

The miRNAs that are indicative of the presence of pancreatic cancer, orhigh risk of developing pancreatic cancer, in a subject can be used fordiagnosing, treating, and/or preventing pancreatic cancer as early aspossible, particularly, when the subject has a pancreatic lesion. Thecurrent invention also provides kits and microRNA microarrays (e.g.,chips) that can be used in the diagnosis of pancreatic cancer orassessing the risk of developing pancreatic cancer in a subject,particularly, when the subject has a pancreatic lesion.

A miRNA is a small non-coding RNA molecule of about 20-25 nucleotidesfound in plants and animals. A miRNA functions in transcriptional andpost-transcriptional regulation of gene expression. Encoded byeukaryotic nuclear DNA, miRNA functions via base-pairing withcomplementary sequences within mRNA molecules, usually resulting in genesilencing via translational repression or target degradation. miRNAs aretranscribed by RNA polymerase II as large RNA precursors calledpri-miRNAs. The pri-miRNAs are processed further in the nucleus toproduce pre-miRNAs. Pre-miRNAs are about 70-nucleotides in length andare folded into imperfect stem-loop structures. The pre-miRNAs are thenexported into the cytoplasm and undergo additional processing togenerate miRNA. A miRNA profile of a sample indicates expression levelsof various miRNAs in the sample.

A differentially expressed miRNA is the miRNA which is eitherover-expressed/up-regulated or under-expressed/down-regulated in asample (e.g., test cell of a tissue sample compared to a control cell,or a cellular or acellular fluid sample, or a reference expression level(a reference value)). A reference expression level may reflect that of a“normal” state (lacking the disease) or the corresponding diseased stateof interest in a relevant population (e.g., an epidemiologicallyrelevant population), for example. In some embodiments, for the purposesof this invention, a miRNA is identified as a “differentially expressedmiRNA” if the miRNA is expressed in the sample at least about 1.8 foldhigher or lower than the corresponding miRNA in the control sample, orreference expression level, or the difference in the expression levelbetween the sample and the control sample or reference expression levelhas statistical significance (p value) of less than 0.05. In someembodiments, miRNA is identified as a “differentially expressed miRNA”if the miRNA is expressed in the sample at about 2- to 4-fold higher orlower than the corresponding miRNA in the control sample or referenceexpression sample.

A profile of differentially expressed miRNAs represents a set of miRNAsthat are differentially expressed in a fluid or tissue sample comparedto a control/reference level. The profile of differentially expressedmiRNAs comprises a profile of down-regulated/under-expressed miRNAs anda profile of up-regulated/over-expressed miRNAs.

Certain embodiments of the current invention provide miRNAs that aredifferentially expressed in a sample of an individual having high riskof developing pancreatic cancer as compared to the corresponding sampleof an individual having low risk of developing pancreatic cancer. In oneembodiment, each of the individual having high risk of developingpancreatic cancer and the individual having low risk of developingpancreatic cancer have a pancreatic lesion, for example, PanIN, MCNs, orIPMNs. The miRNAs that are differentially expressed in a cell of anindividual having high risk of developing or having pancreatic cancercan be used as biomarkers for diagnosis and/or prevention of pancreaticcancer. For example, miRNAs differentially expressed in a cell of anindividual having high risk of developing pancreatic cancer as comparedto the corresponding cell of an individual having low risk of developingpancreatic cancer comprises one or more of, miR-100, miR-99b, miR-99a,miR-342-3p, miR-126, miR-888, miR-130a, let-7c, miR-150, miR-296,miR-199a, miR-199a-3p, and miR-302a, preferably, one or more of miR-100,miR-99b, miR-99a, miR-342-3p, miR-126, and miR-130a.

Various embodiments provide a profile of differentially expressed miRNAsin a sample of an individual having pancreatic cancer, or having highrisk of developing pancreatic cancer, particularly, when the individualhas a pancreatic lesion. The profile of differentially expressed miRNAsin a sample of an individual having pancreatic cancer, or having a highrisk of developing pancreatic cancer, comprises use of a profile ofup-regulated/over-expressed miRNAs and a profile ofdown-regulated/under-expressed miRNAs.

In some embodiments, the method for detecting in a subject the presenceof pancreatic cancer, or a high risk of developing pancreatic cancer,comprises:

(a) detecting the level of expression of one or more miRNAs in a samplefrom the subject; and

(b) comparing the detected expression level to a reference expressionlevel, wherein a differential expression of the one or more miRNAs inthe sample, as compared to the reference expression level, is indicativeof the presence of pancreatic cancer, or a higher risk of developingpancreatic cancer, versus the absence of pancreatic cancer, or a lowerrisk of developing pancreatic cancer, respectively.

The differential expression of the one or more miRNAs in the sample, ascompared to the reference expression level, may be indicative of apancreatic cancer precursor (such as intraductal papillary mucinousneoplasm (IPMN)) versus non-IPMN (normal cells).

The differential expression of the one or more miRNAs in the sample, ascompared to the reference expression level, may be indicative of amalignant intraductal papillary mucinous neoplasm (IPMN) versus a benignIPMN.

In some embodiments, the sample is a tissue sample, and the one or moremiRNAs belong to a profile of miRNAs that are differentially expressedin a cell of an individual having a higher risk of developing pancreaticcancer as compared to the corresponding cell of an individual havinglower risk of developing pancreatic cancer.

In some embodiments, the subject has a pancreatic lesion and the one ormore miRNAs belong to a profile of differentially expressed miRNAs in asample of an individual having a pancreatic lesion and having higherrisk of developing pancreatic cancer compared to the correspondingsample of an individual having a pancreatic lesion and having lower riskof developing pancreatic cancer.

Various methods may be used for detecting the expression level of one ormore miRNAs in a sample. For example, measurement of miRNA can becarried out by barcode-based assay, miRNA microarray analysis (e.g.,chip), digital polymerase chain reaction (PCR), real-time PCR,quantitative reverse transcription PCR (qRT-PCR), semi-quantitative PCR,Northern blot, or in situ hybridization. Typically, the mature miRNA ismeasured, for example, using an in vitro assay.

In some embodiments, a profile of differentially expressed miRNAscomprise of one or more (optionally, all) of miR-100, miR-99b, miR-99a,miR-342-3p, miR-126, miR-888, miR-130a, let-7c, miR-150, miR-296,miR-199a, miR-199a-3p, and miR-302a. In some embodiments, the sample isa tissue sample.

In some embodiments, a profile of differentially expressed miRNAscomprise of one or more (optionally, all) of let-7a-5p, let-7d-5p,let-7f-5p, let-7g-5p, let-7i-5p, miR-107, miR-1260b, miR-126-3p,miR-142-3p, miR-145-5p, miR-146a-5p, miR-148a-3p, miR-15b-5p,miR-181a-5p, miR-191-5p, miR-199a-3p, miR-199b-3p, miR-20a-5p,miR-20b-5p, miR-22-3p, miR-23a-3p, miR-24-3p, miR-26a-5p, miR-27a-3p,miR-29c-3p, miR-335-5p, miR-337-5p, miR-340-5p, miR-423-5p, miR-4454,miR-593-3p, and miR-98, which is useful in distinguishing IPMN fromnon-IPMN. If higher expression of one or more (optionally, all) of thesemiRNA markers is detected relative to the reference expression level, itsuggests a precursor legion is present. Optionally, a confirmatory testmay be administered, such as imaging. In some embodiments using thesemiRNAs, the sample is a fluid sample, such as whole blood, serum,plasma, urine, or pancreatic cyst fluid.

In some embodiments, a profile of differentially expressed miRNAscomprise of one or more (optionally, all) of miR-200a-3p, miR-1185-5p,miR-33a-5p, miR-574-3p, and miR-663b, which can distinguish malignantIPMN from benign IPMN. If lower expression of one or more (optionally,all) of these miRNA markers is detected relative to the referenceexpression level, it suggests the subject has a pancreatic malignancy,and therapeutic treatment should be administered such as a surgicalintervention (e.g., resection or Whipple procedure), or administrationof an anti-cancer agent (e.g., chemotherapeutic or immunotherapy), orradiation. In some embodiments using these miRNAs, the sample is a fluidsample, such as whole blood, serum, plasma, urine, or pancreatic cystfluid.

Various samples can be used for practicing the methods of the currentinvention. Non-limiting examples of the tissues or cell samples that canbe used to practice the methods of the current invention include brain,eyes, Pineal gland, Pituitary gland, Thyroid gland, Parathyroid glands,thorax, heart, lungs, esophagus, Thymus gland, pleura, Adrenal glands,Appendix, Gall bladder, urinary bladder, large intestine, smallintestine, kidneys, liver, pancrease, spleen, stoma, Prostate gland,Testes, ovaries, or uterus. Also, samples of body fluids of a subjectcan be used to practice the methods of the current invention.Non-limiting examples of the body fluids that can be used to practicethe methods of the current invention include amniotic fluid, aqueoushumor, vitreous humor, bile, cerebrospinal fluid, chyle, endolymph,perilymph, female ejaculate, male ejaculate, lymph, mucus (includingnasal drainage and phlegm), pericardial fluid, peritoneal fluid, pleuralfluid, pus, rheum, saliva, sputum, synovial fluid, vaginal secretion,pancreatic juice or aspirate (20, 47), pancreatic cyst fluid (28),urine, serum, plasma, and blood. In some embodiments, the sample is ablood sample (whole blood, serum, or plasma). In one embodiment, bloodcells are used to practice the methods of the current invention. Variousprocessing steps known in the art may be carried out on a sample toobtain genetic material from the blood cells to determine the expressionlevel of one or more miRNAs.

In another embodiment, the miRNAs indicative of pancreatic cancer, or ahigher risk of developing pancreatic cancer, are detected in bodyfluids. In some embodiments, the body fluid is a cell-containing bodyfluid, such as whole blood. In some embodiments, the body fluid is acell-free fluid such as plasma. The samples obtained from the subjectcan be appropriately treated to separate the fraction containing cellsfrom the fraction containing the fluid. Non-limiting examples of suchtreatment includes filtration, centrifugation, etc. Tissue samples maybe fresh frozen or formalin-fixed, paraffin-embedded, for example.

Various body fluids that can be used to practice these methods of theclaimed invention include amniotic fluid, aqueous humor, vitreous humor,bile, cerebrospinal fluid, chyle, endolymph, perilymph, femaleejaculate, male ejaculate, lymph, mucus (including nasal drainage andphlegm), pericardial fluid, peritoneal fluid, pleural fluid, pus, rheum,saliva, sputum, synovial fluid, vaginal secretion, pancreatic juice oraspirate (20, 47), pancreatic cyst fluid (28), serum, plasma, and blood.In some embodiments, the sample is a blood sample (whole blood, serum,or plasma). In some embodiments, the sample is an acellular body fluid,such as serum or blood plasma.

Certain other embodiments of the current invention provide microarraysof oligonucleotides corresponding to the miRNAs that are differentiallyexpressed in a sample of an individual having pancreatic cancer, orhaving a high risk of developing pancreatic cancer, particularly, whenthe individual has a pancreatic lesion. In one embodiment, the cell is ablood cell and accordingly, the current invention also provides ablood-based minimally-invasive miRNA assay that can be used to identifyin an individual having a pancreatic lesion the risk of developingpancreatic cancer. As such, the current invention provides microarraysthat can be used to differentiate between high-risk pancreatic lesionsthat warrant resection and low-risk pancreatic lesions that can bemonitored. In some embodiments, the microarrays of the current inventioncomprise oligonucleotides corresponding to one or more of miR-100,miR-99b, miR-99a, miR-342-3p, miR-126, miR-888, miR-130a, let-7c,miR-150, miR-296, miR-199a, miR-199a-3p, and miR-302a, preferably, oneor more of miR-100, miR-99b, miR-99a, miR-342-3p, miR-126, and miR-130a.

In some embodiments, the microarrays of the current invention compriseoligonucleotides corresponding to one or more of let-7a-5p, let-7d-5p,let-7f-5p, let-7g-5p, let-7i-5p, miR-107, miR-1260b, miR-126-3p,miR-142-3p, miR-145-5p, miR-146a-5p, miR-148a-3p, miR-15b-5p,miR-181a-5p, miR-191-5p, miR-199a-3p, miR-199b-3p, miR-20a-5p,miR-20b-5p, miR-22-3p, miR-23a-3p, miR-24-3p, miR-26a-5p, miR-27a-3p,miR-29c-3p, miR-335-5p, miR-33′7-5p, miR-340-5p, miR-423-5p, miR-4454,miR-593-3p, and miR-98.

In some embodiments, the microarrays of the current invention compriseoligonucleotides corresponding to one or more of miR-200a-3p,miR-1185-5p, miR-33a-5p, miR-574-3p, and miR-663b.

In some embodiments, the microarrays of the current invention compriseoligonucleotides corresponding to one or more of miR-1185-5p,miR-33a-5p, miR-574-3p, and miR-663b.

Additional embodiments of the current invention provide microarray chipsconsisting essentially of oligonucleotides corresponding to miRNAsbelonging to a profile of differentially expressed miRNAs in a sample ofan individual having pancreatic cancer, or having a high risk ofdeveloping pancreatic cancer, particularly, when the individual has apancreatic lesion. For the purposes of this invention, a microarray chip“consisting essentially of” oligonucleotides corresponding to miRNAsbelonging to a profile of differentially expressed miRNAs in a sample ofan individual having pancreatic cancer, or having a high risk ofdeveloping pancreatic cancer, indicates that the microarray chipcontains only those miRNAs that are differentially expressed in thesample of an individual having pancreatic cancer, or having high risk ofdeveloping pancreatic cancer, and does not contain miRNA whoseexpression remains unchanged in the sample of an individual havingpancreatic cancer, or high risk of developing pancreatic cancer.

In one embodiment of the current invention, a microarray chip consistsessentially of oligonucleotides corresponding to one or more of,miR-100, miR-99b, miR-99a, miR-342-3p, miR-126, miR-888, miR-130a,let-7c, miR-150, miR-296, miR-199a, miR-199a-3p, and miR-302a,preferably, one or more of miR-100, miR-99b, miR-99a, miR-342-3p,miR-126, and miR-130a.

Certain embodiments of the current invention provide a method ofscreening a subject for having high risk of developing pancreaticcancer, the method comprising:

a) obtaining a test cell from the subject,

b) obtaining a reference cell,

c) determining the expression of an miRNA in the test cell and thereference cell wherein the miRNA belongs to a profile of differentiallyexpressed miRNAs in a cell of an individual having high risk ofdeveloping pancreatic cancer,

d) comparing the expression of the miRNA in the test cell with theexpression of the miRNA in the reference cell,

e) determining the presence of high risk of developing pancreatic cancerin the subject if the miRNA is differentially expressed in the test cellas compared to the reference cell.

In one embodiment, the subject being screened for having high risk ofdeveloping pancreatic cancer has a pancreatic lesion and the miRNAbelongs to a profile of differentially expressed miRNAs in a cell of anindividual having a pancreatic lesion and having high risk of developingpancreatic cancer compared to the corresponding cell of an individualhaving the pancreatic lesion and having no risk or low risk ofdeveloping pancreatic cancer.

The reference sample can be obtained from an individual having no riskor low risk of developing pancreatic cancer. The reference sample canalso be obtained from an individual who has a pancreatic lesion and whohas no risk or low risk of developing pancreatic cancer. Additionally,the reference sample can be obtained from the subject (and stored forfuture use) when the subject was known to have no risk or low risk ofdeveloping pancreatic cancer, particularly, when the subject had apancreatic lesion and had no risk or low risk of developing pancreaticcancer. The methods of the current invention can be practiced in amammal, for example, a human, an ape, a pig, a bovine, a rodent, or afeline.

In some embodiments of the methods of the invention, the subject fromwhich the sample is obtained has pancreatic cancer. In some embodimentsof the methods of the invention, the subject from which the sample isobtained does not have pancreatic cancer.

The miRNA that can be tested according to the methods of the currentinvention can be one or more of miR-100, miR-99b, miR-99a, miR-342-3p,miR-126, miR-888, miR-130a, let-7c, miR-150, miR-296, miR-199a,miR-199a-3p, and miR-302a, preferably, one or more of miR-100, miR-99b,miR-99a, miR-342-3p, miR-126, and miR-130a.

In an embodiment, the method of screening a subject for havingpancreatic cancer, or for having a high risk of developing pancreaticcancer comprises determining the expression of a plurality of miRNAs,wherein each miRNA belongs to the profile of differentially expressedmiRNAs in a cell of an individual having high risk of developingpancreatic cancer. In one embodiment, the subject being screened forhaving high risk of developing pancreatic cancer has a pancreatic lesionand the plurality of miRNAs belong to a profile of differentiallyexpressed miRNAs in a cell of an individual having a pancreatic lesionand having high risk of developing pancreatic cancer.

A plurality of miRNAs used in the method of screening a subject forhaving pancreatic cancer, or having a high risk of developing pancreaticcancer, can be selected from miR-100, miR-99b, miR-99a, miR-342-3p,miR-126, miR-888, miR-130a, let-7c, miR-150, miR-296, miR-199a,miR-199a-3p, and miR-302a, preferably, from miR-100, miR-99b, miR-99a,miR-342-3p, miR-126, and miR-130a.

In other embodiments, the miRNA is one or more of let-7a-5p, let-7d-5p,let-7f-5p, let-7g-5p, let-7i-5p, miR-107, miR-1260b, miR-126-3p,miR-142-3p, miR-145-5p, miR-146a-5p, miR-148a-3p, miR-15b-5p,miR-181a-5p, miR-191-5p, miR-199a-3p, miR-199b-3p, miR-20a-5p,miR-20b-5p, miR-22-3p, miR-23a-3p, miR-24-3p, miR-26a-5p, miR-27a-3p,miR-29c-3p, miR-335-5p, miR-337-5p, miR-340-5p, miR-423-5p, miR-4454,miR-593-3p, and miR-98.

In other embodiments, the miRNAs are one or more of miR-200a-3p,miR-1185-5p, miR-33a-5p, miR-574-3p, and miR-663b.

In other embodiments, the miRNAs are one or more of miR-1185-5p,miR-33a-5p, miR-574-3p, and miR-663b.

Additional embodiments of the current invention provide kits forperforming a barcode-based (e.g., NanoString™ based) assay to quantifyexpression of miRNAs belonging to a profile of differentially expressedmiRNAs in a sample of an individual having pancreatic cancer, or havinga high risk of developing pancreatic cancer, particularly, when theindividual has a pancreatic lesion. NanoString™ based assays aredescribed in the U.S. Pat. Nos. 8,415,102, 8,519,115, and 7,919,237,which are herein incorporated by reference in their entirety.NanoString's NCOUNTER technology is a variation on the DNA microarray.It uses molecular “barcodes” and microscoping imaging to detect andcount up to several hundred unique transcripts in one hybridizationreaction. Each color-coded barcode is attached to a singletarget-specific probe corresponding to a target of interest. Theprotocol typically includes hybridization (employing two ˜50 base probesper mRNA that hybridize in solution; the reporter probe carries thesignal, while the capture probe allows the complex to be immobilized fordata collection); purification and immobilization (after hybridization,the excess probes are removed and the probe/target complexes are alignedand immobilized in the cartridge); and data collection (samplecartridges are placed in a digital analyzer instrument for datacollection; color codes on the surface of the cartridge are counted andtabulated for each target molecule). The protocol is carried out with aprep station, which is an automated fluidic instrument that immobilizescode set complexes for data collection, and a digital analyzer, whichderives data by counting fluorescent barcodes. Code set complexes arecustom-made or pre-designed sets of color-coded probes pre-mixed with aset of system controls. A person of ordinary skill in the art candetermine the sequences of various probes for barcode-based assay topractice the claimed invention and such embodiments are within thepurview of the current invention.

In one embodiment of the current invention, the barcode-based assay kitconsists essentially of oligonucleotide probes designed to quantify oneor more of, miR-100, miR-99b, miR-99a, miR-342-3p, miR-126, miR-888,miR-130a, let-7c, miR-150, miR-296, miR-199a, miR-199a-3p, and miR-302a,preferably, one or more of miR-100, miR-99b, miR-99a, miR-342-3p,miR-126, and miR-130a.

In other embodiments, the miRNA is one or more of let-7a-5p, let-7d-5p,let-7f-5p, let-7g-5p, let-7i-5p, miR-107, miR-1260b, miR-126-3p,miR-142-3p, miR-145-5p, miR-146a-5p, miR-148a-3p, miR-15b-5p,miR-181a-5p, miR-191-5p, miR-199a-3p, miR-199b-3p, miR-20a-5p,miR-20b-5p, miR-22-3p, miR-23a-3p, miR-24-3p, miR-26a-5p, miR-27a-3p,miR-29c-3p, miR-335-5p, miR-337-5p, miR-340-5p, miR-423-5p, miR-4454,miR-593-3p, and miR-98.

In other embodiments, the miRNAs are one or more of miR-200a-3p,miR-1185-5p, miR-33a-5p, miR-574-3p, and miR-663b.

In other embodiments, the miRNAs are one or more of miR-1185-5p,miR-33a-5p, miR-574-3p, and miR-663b.

For the purposes of this invention, a barcode-based (e.g., NanoString™based) assay kit “consisting essentially of” oligonucleotide probesdesigned to quantify miRNAs belonging to a profile of differentiallyexpressed miRNAs in a cell of an individual having pancreatic cancer, ora high risk of developing pancreatic cancer, indicates that thebarcode-based assay kit contains oligonucleotide probes correspondingonly those miRNAs that are differentially expressed in the sample of anindividual having pancreatic cancer, or having a high risk of developingpancreatic cancer, and does not contain oligonucleotide probescorresponding to miRNA whose expression remains unchanged in the sampleof an individual having pancreatic cancer, or having a high risk ofdeveloping pancreatic cancer.

Additional embodiments of the current invention provide methods oftreating and/or preventing pancreatic cancer in a subject identified tobe having high risk of developing pancreatic cancer, particularly, whenthe subject has a pancreatic lesion. The method of treating and/orpreventing pancreatic cancer in the subject comprises administering apharmaceutically effective amount of a pancreatic cancer therapeutic oradministering one or more other therapies (for example, radiotherapy,chemotherapy, immunotherapy, another type of anti-cancer agent, surgery,or a combination of two or more of the foregoing), directed at treatingand/or preventing pancreatic cancer. As used herein, the term“preventing” encompasses avoiding develop of the cancer, as well asdelaying the onset of the cancer. In certain embodiments a combinationof two or more therapies directed at treating pancreatic cancer areadministered to the subject.

As used herein, the article “a” (such as “a cell”) refers to one or morethan one.

In one embodiment, the therapy directed at treating and/or preventingpancreatic cancer comprises a surgical resection of the pancreaticlesion from the subject, or a Whipple procedure, or other therapy forpancreatic cancer, such as administration of an anti-cancer agent (e.g.,chemotherapeutic or immunotherapy).

Accordingly, the current invention provides a method of treating and/orpreventing a pancreatic cancer in a subject, the method comprising:

(a) detecting the level of expression of one or more miRNAs in:

-   -   A) a test cell obtained from the subject, and    -   B) optionally, a control cell,

wherein a differential expression of the one or more miRNAs in the cellsample obtained from the subject as compared to the control cell, or areference expression level, is indicative of the presence high risk ofdeveloping pancreatic cancer in the subject; and

(b) administering a therapy to the mammal to treat the pancreaticcancer,

wherein the one or more miRNAs are differentially expressed in a cell inan individual having high risk of developing pancreatic cancer ascompared to the corresponding cell in an individual having low risk ofdeveloping pancreatic cancer.

In one embodiment, the subject being screened for having high risk ofdeveloping pancreatic cancer has a pancreatic lesion and the miRNA isdifferentially expressed in a cell of an individual having a pancreaticlesion and having high risk of developing pancreatic cancer compared tothe corresponding cell of an individual having a pancreatic lesion andhaving no risk or low risk of developing pancreatic cancer.

In one embodiment, the cell sample obtained from the subject is a bloodcell sample.

In another embodiment, the current invention also provides a method forpredicting the existence of a pancreatic cancer in a subject, the methodcomprising:

a) obtaining a cell sample from the subject,

b) optionally, obtaining a control cell, and

c) detecting and quantifying the expression of one or more miRNAs thatare differentially expressed in a cell of an individual having high riskof developing pancreatic cancer as compared to the corresponding cell ofan individual having low risk of developing pancreatic cancer, whereinquantifying the expression of the one or more miRNAs is performed bynorthern blot analysis, micro-array based method, real-time quantitativePCR, or semi-quantitative RT-PCR.

In one embodiment of the method for predicting the existence of apancreatic cancer in a subject, the subject being screened for havinghigh risk of developing pancreatic cancer has a pancreatic lesion andthe miRNA is differentially expressed in a cell of an individual havinga pancreatic lesion and having high risk of developing pancreatic cancercompared to the corresponding cell of an individual having a pancreaticlesion and having no risk or low risk of developing pancreatic cancer.

In a further embodiment, the method of detecting the presence ofpancreatic cancer, or detecting the high risk of developing pancreaticcancer, can be performed by a computer-assisted analytic device. In thecomputer assisted method, the computer-assisted analytical devicedetects the differential expression of miRNAs, determines the amounts ofsaid detected miRNAs, and performs a comparison of the determinedamount(s) obtained from the analyzing unit with a reference amount orreference amounts to provide output regarding the presence or absence ofhigh risk of developing pancreatic cancer in the subject, particularly,when the subject has a pancreatic lesion. In certain embodiments, thecomputer-assisted analytical device detects differentially expressedmiRNAs selected from one or more of miR-100, miR-99b, miR-99a,miR-342-3p, miR-126, miR-888, miR-130a, let-7c, miR-150, miR-296,miR-199a, miR-199a-3p, and miR-302a, particularly, one or more ofmiR-100, miR-99b, miR-99a, miR-342-3p, miR-126, miR-130a and determinesthe amounts of said detected miRNAs and performs a comparison of thedetermined amount(s) obtained from the analyzing unit with a referenceamount or reference amounts to provide output regarding the presence orabsence of high risk of developing pancreatic cancer in the subject.

EXEMPLIFIED EMBODIMENTS

Embodiment 1: A method of treating and/or preventing the development ofpancreatic cancer in a subject, the method comprising:

(a) detecting the level of expression of one or more miRNAs in a samplefrom the subject;

(b) comparing the detected expression level to a reference expressionlevel, wherein a differential expression of the one or more miRNAs inthe sample, as compared to the reference expression level, is indicativeof the presence of pancreatic cancer, or a higher risk of developingpancreatic cancer, versus the absence of pancreatic cancer, or a lowerrisk of developing pancreatic cancer, respectively; and

(c) administering a therapy to treat and/or prevent the pancreaticcancer to the subject identified as having the pancreatic cancer, or ata higher risk of developing pancreatic cancer.

Embodiment 2: The method of embodiment 1, wherein a differentialexpression of the one or more miRNAs in the sample, as compared to thereference expression level, is indicative of a pancreatic cancerprecursor (such as intraductal papillary mucinous neoplasm (IPMN))versus non-IPMN (normal cells).

Embodiment 3: The method of embodiment 1, wherein a differentialexpression of the one or more miRNAs in the sample, as compared to thereference expression level, is indicative of a malignant intraductalpapillary mucinous neoplasm (IPMN) versus a benign IPMN.

Embodiment 4: The method of embodiment 1, wherein the sample is a tissuesample, and wherein the one or more miRNAs belong to a profile of miRNAsthat are differentially expressed in a cell of an individual having ahigher risk of developing pancreatic cancer as compared to thecorresponding cell of an individual having lower risk of developingpancreatic cancer.

Embodiment 5: The method of embodiment 1, wherein the subject has apancreatic lesion and the one or more miRNAs belong to a profile ofdifferentially expressed miRNAs in a sample of an individual having apancreatic lesion and having higher risk of developing pancreatic cancercompared to the corresponding sample of an individual having apancreatic lesion and having lower risk of developing pancreatic cancer.

Embodiment 6: The method of embodiment 1, wherein the sample obtainedfrom the subject is a tissue sample.

Embodiment 7: The method of embodiment 6, wherein the tissue sample isfresh frozen or formalin-fixed, paraffin-embedded prior to saiddetecting.

Embodiment 8: The method of embodiment 1, wherein the sample obtainedfrom the subject is a fluid sample.

Embodiment 9: The method of embodiment 1, wherein the sample obtainedfrom the subject is whole blood, serum, or plasma.

Embodiment 10: The method of embodiment 1, wherein the pancreatic canceris pancreatic ductal adenocarcinoma (PDAC).

Embodiment 11: The method of embodiment 3, wherein the pancreatic lesionis intraepithelial neoplasia (PanIN), mucinous cystic neoplasms (MCNs),or intraductal papillary mucinous neoplasms (IPMNs).

Embodiment 12: The method of embodiment 1, wherein the one or moremiRNAs are selected from miR-100, miR-99b, miR-99a, miR-342-3p, miR-126,miR-888, miR-130a, let-7c, miR-150, miR-296, miR-199a, miR-199a-3p, andmiR-302a.

Embodiment 13: The method of embodiment 12, wherein the sample obtainedfrom the subject is a tissue sample.

Embodiment 14: The method of embodiment 1, wherein the one or more mRNAsare selected from among let-7a-5p, let-7d-5p, let-7f-5p, let-7g-5p,let-7i-5p, miR-107, miR-1260b, miR-126-3p, miR-142-3p, miR-145-5p,miR-146a-5p, miR-148a-3p, miR-15b-5p, miR-181a-5p, miR-191-5p,miR-199a-3p, miR-199b-3p, miR-20a-5p, miR-20b-5p, miR-22-3p, miR-23a-3p,miR-24-3p, miR-26a-5p, miR-27a-3p, miR-29c-3p, miR-335-5p, miR-337-5p,miR-340-5p, miR-423-5p, miR-4454, miR-593-3p, and miR-98.

Embodiment 15: The method of embodiment 1, wherein the sample obtainedfrom the subject is a plasma sample.

Embodiment 16: The method of embodiment 1, wherein the one or more mRNAsare selected from among miR-200a-3p, miR-1185-5p, miR-33a-5p,miR-574-3p, and miR-663b.

Embodiment 17: The method of embodiment 16, wherein the sample obtainedfrom the subject is a plasma sample.

Embodiment 18: The method of embodiment 1, wherein the one or more mRNAsare selected from among miR-1185-5p, miR-33a-5p, miR-574-3p, andmiR-663b.

Embodiment 19: The method of embodiment 1, wherein the sample obtainedfrom the subject is a plasma sample.

Embodiment 20. The method of embodiment 1, wherein said detectingcomprises measuring the expression of the one or more miRNAs bybarcode-based assay, miRNA microarray analysis (e.g., chip), digitalpolymerase chain reaction (PCR), real-time PCR, quantitative reversetranscription PCR (qRT-PCR), semi-quantitative PCR, Northern blot, or insitu hybridization.

Embodiment 21: The method of any preceding embodiment, wherein thesubject is a human.

Embodiment 22: The method of embodiment 1, wherein the therapy comprisesa surgical resection of the pancreatic lesion or Whipple procedure.

Embodiment 23: The method of embodiment 1 or 22, wherein the therapycomprises administration of an anti-cancer agent (e.g., achemotherapeutic or immunotherapy) to the subject.

Embodiment 24: A method of treating and/or preventing pancreatic cancerin a subject, comprising measuring the level of expression of one ormore miRNAs in a sample obtained from the subject; and administering atreatment for the pancreatic cancer, wherein the one or more miRNAscomprise:

(a) one or more mRNAs selected from among miR-100, miR-99b, miR-99a,miR-342-3p, miR-126, miR-888, miR-130a, let-7c, miR-150, miR-296,miR-199a, miR-199a-3p, and miR-302a; or

(b) one or more mRNAs selected from among let-7a-5p, let-7d-5p,let-7f-5p, let-7g-5p, let-7i-5p, miR-107, miR-1260b, miR-126-3p,miR-142-3p, miR-145-5p, miR-146a-5p, miR-148a-3p, miR-15b-5p,miR-181a-5p, miR-191-5p, miR-199a-3p, miR-199b-3p, miR-20a-5p,miR-20b-5p, miR-22-3p, miR-23a-3p, miR-24-3p, miR-26a-5p, miR-27a-3p,miR-29c-3p, miR-335-5p, miR-337-5p, miR-340-5p, miR-423-5p, miR-4454,miR-593-3p, and miR-98; or

(c) one or more mRNAs selected from among miR-200a-3p, miR-1185-5p,miR-33a-5p, miR-574-3p, and miR-663b.

Embodiment 25: The method of embodiment 24, wherein the one or moremiRNAs comprise one or more from among miR-1185-5p, miR-33a-5p,miR-574-3p, and miR-663b.

Embodiment 26: The method of embodiment 24, wherein said detectingcomprises measuring the expression of the one or more miRNAs bybarcode-based assay, miRNA microarray analysis (e.g., chip), digitalpolymerase chain reaction (PCR), real-time PCR, quantitative reversetranscription PCR (qRT-PCR), semi-quantitative PCR, Northern blot, or insitu hybridization.

Embodiment 27: A microarray chip corresponding to a profile of miRNAsthat are differentially expressed in a sample of an individual havingpancreatic cancer, or having a high risk of developing pancreaticcancer, as compared to the corresponding sample of an individual havingno risk or low risk of developing pancreatic cancer, the microarray chipconsisting essentially of oligonucleotides corresponding to one or moreof miRNA selected from among miR-100, miR-99b, miR-99a, miR-342-3p,miR-126, miR-888, miR-130a, let-7c, miR-150, miR-296, miR-199a,miR-199a-3p, and miR-302a.

Embodiment 28: The microarray chip of embodiment 27, wherein theoligonucleotides correspond to each of miR-100, miR-99b, miR-99a,miR-342-3p, miR-126, miR-888, miR-130a, let-7c, miR-150, miR-296,miR-199a, miR-199a-3p, and miR-302a.

Embodiment 29: A microarray chip corresponding to a profile of miRNAsthat are differentially expressed in a sample of an individual having apancreatic lesion and having high risk of developing pancreatic cancercompared to the corresponding sample of an individual having thepancreatic lesion and having no risk or low risk of developingpancreatic cancer, the microarray chip consisting essentially ofoligonucleotides corresponding to one or more selected from amongmiR-100, miR-99b, miR-99a, miR-342-3p, miR-126, miR-888, miR-130a,let-7c, miR-150, miR-296, miR-199a, miR-199a-3p, and miR-302a.

Embodiment 30: The microarray chip of embodiment 29, wherein theoligonucleotides correspond to each of miR-100, miR-99b, miR-99a,miR-342-3p, miR-126, miR-888, miR-130a, let-7c, miR-150, miR-296,miR-199a, miR-199a-3p, and miR-302a.

Embodiment 31: A microarray chip corresponding to a profile of miRNAsthat are differentially expressed in a sample of an individual having apancreatic cancer precursor (such as intraductal papillary mucinousneoplasm (IPMN)) as compared to a non-IPMN (normal cells), themicroarray chip consisting essentially of oligonucleotides correspondingto one or more of miRNA selected from among one or more miRNA selectedfrom among let-7a-5p, let-7d-5p, let-7f-5p, let-7g-5p, let-7i-5p,miR-107, miR-1260b, miR-126-3p, miR-142-3p, miR-145-5p, miR-146a-5p,miR-148a-3p, miR-15b-5p, miR-181a-5p, miR-191-5p, miR-199a-3p,miR-199b-3p, miR-20a-5p, miR-20b-5p, miR-22-3p, miR-23a-3p, miR-24-3p,miR-26a-5p, miR-27a-3p, miR-29c-3p, miR-335-5p, miR-337-5p, miR-340-5p,miR-423-5p, miR-4454, miR-593-3p, and miR-98.

Embodiment 32: The microarray chip of embodiment 31, wherein theoligonucleotides correspond to each of let-7a-5p, let-7d-5p, let-7f-5p,let-7g-5p, let-7i-5p, miR-107, miR-1260b, miR-126-3p, miR-142-3p,miR-145-5p, miR-146a-5p, miR-148a-3p, miR-15b-5p, miR-181a-5p,miR-191-5p, miR-199a-3p, miR-199b-3p, miR-20a-5p, miR-20b-5p, miR-22-3p,miR-23a-3p, miR-24-3p, miR-26a-5p, miR-27a-3p, miR-29c-3p, miR-335-5p,miR-337-5p, miR-340-5p, miR-423-5p, miR-4454, miR-593-3p, and miR-98.

Embodiment 33: A microarray chip corresponding to a profile of miRNAsthat are differentially expressed in a sample of an individual having amalignant intraductal papillary mucinous neoplasm (IPMN)) as compared toa benign IPMN, the microarray chip consisting essentially ofoligonucleotides corresponding to one or more of miRNA selected fromamong one or more miRNA selected from among miR-200a-3p, miR-1185-5p,miR-33a-5p, miR-5′74-3p, and miR-663b.

Embodiment 34: The microarray chip of embodiment 33, wherein theoligonucleotides correspond to each of miR-200a-3p, miR-1185-5p,miR-33a-5p, miR-574-3p, and miR-663b.

Embodiment 35: The microarray chip of embodiment 33, wherein the one ormore miRNAs comprise one or more from among miR-1185-5p, miR-33a-5p,miR-574-3p, and miR-663b.

Embodiment 36: The microarray chip of embodiment 33, wherein theoligonucleotides correspond to each of miR-1185-5p, miR-33a-5p,miR-574-3p, and miR-663b.

Embodiment 37: A method for detecting in a subject the presence ofpancreatic cancer, or a high risk of developing pancreatic cancer, themethod comprising:

(a) detecting the level of expression of one or more miRNAs in a samplefrom the subject; and

(b) comparing the detected expression level to a reference expressionlevel, wherein a differential expression of the one or more miRNAs inthe sample, as compared to the reference expression level, is indicativeof the presence of pancreatic cancer, or a higher risk of developingpancreatic cancer, versus the absence of pancreatic cancer, or a lowerrisk of developing pancreatic cancer, respectively.

Embodiment 38: The method of embodiment 37, wherein a differentialexpression of the one or more miRNAs in the sample, as compared to thereference expression level, is indicative of a pancreatic cancerprecursor (such as intraductal papillary mucinous neoplasm (IPMN))versus non-IPMN (normal cells).

Embodiment 39: The method of embodiment 37, wherein a differentialexpression of the one or more miRNAs in the sample, as compared to thereference expression level, is indicative of a malignant intraductalpapillary mucinous neoplasm (IPMN) versus a benign IPMN.

Embodiment 40: The method of embodiment 37, wherein the sample is atissue sample, and wherein the one or more miRNAs belong to a profile ofmiRNAs that are differentially expressed in a cell of an individualhaving a higher risk of developing pancreatic cancer as compared to thecorresponding cell of an individual having lower risk of developingpancreatic cancer.

Embodiment 41: The method of embodiment 37, wherein the subject has apancreatic lesion and the one or more miRNAs belong to a profile ofdifferentially expressed miRNAs in a sample of an individual having apancreatic lesion and having higher risk of developing pancreatic cancercompared to the corresponding sample of an individual having apancreatic lesion and having lower risk of developing pancreatic cancer.

Embodiment 42: The method of embodiment 37, wherein the sample obtainedfrom the subject is a tissue sample.

Embodiment 43: The method of embodiment 42, wherein the tissue sample isfresh frozen or formalin-fixed, paraffin-embedded prior to saiddetecting.

Embodiment 44: The method of embodiment 37, wherein the sample obtainedfrom the subject is a fluid sample.

Embodiment 45: The method of embodiment 44, wherein the fluid sampleobtained from the subject is whole blood, serum, plasma, urine, orpancreatic cyst fluid.

Embodiment 46: The method of embodiment 37, wherein the pancreaticcancer is pancreatic ductal adenocarcinoma (PDAC).

Embodiment 47: The method of embodiment 41, wherein the pancreaticlesion is intraepithelial neoplasia (PanIN), mucinous cystic neoplasms(MCNs), or intraductal papillary mucinous neoplasms (IPMNs).

Embodiment 48: The method of embodiment 37, wherein the one or moremiRNAs are selected from miR-100, miR-99b, miR-99a, miR-342-3p, miR-126,miR-888, miR-130a, let-7c, miR-150, miR-296, miR-199a, miR-199a-3p, andmiR-302a.

Embodiment 49: The method of embodiment 37, wherein the one or moremiRNAs are each of miR-100, miR-99b, miR-99a, miR-342-3p, miR-126,miR-888, miR-130a, let-7c, miR-150, miR-296, miR-199a, miR-199a-3p, andmiR-302a.

Embodiment 50: The method of embodiment 37, wherein the sample obtainedfrom the subject is a tissue sample.

Embodiment 51: The method of embodiment 37, wherein the one or moremRNAs are selected from among let-7a-5p, let-7d-5p, let-7f-5p,let-7g-5p, let-7i-5p, miR-107, miR-1260b, miR-126-3p, miR-142-3p,miR-145-5p, miR-146a-5p, miR-148a-3p, miR-15b-5p, miR-181a-5p,miR-191-5p, miR-199a-3p, miR-199b-3p, miR-20a-5p, miR-20b-5p, miR-22-3p,miR-23a-3p, miR-24-3p, miR-26a-5p, miR-27a-3p, miR-29c-3p, miR-335-5p,miR-337-5p, miR-340-5p, miR-423-5p, miR-4454, miR-593-3p, and miR-98.

Embodiment 52: The method of embodiment 37, wherein the one or moremRNAs are each of let-7a-5p, let-7d-5p, let-7f-5p, let-7g-5p, let-7i-5p,miR-107, miR-1260b, miR-126-3p, miR-142-3p, miR-145-5p, miR-146a-5p,miR-148a-3p, miR-15b-5p, miR-181a-5p, miR-191-5p, miR-199a-3p,miR-199b-3p, miR-20a-5p, miR-20b-5p, miR-22-3p, miR-23a-3p, miR-24-3p,miR-26a-5p, miR-27a-3p, miR-29c-3p, miR-335-5p, miR-337-5p, miR-340-5p,miR-423-5p, miR-4454, miR-593-3p, and miR-98.

Embodiment 53: The method of embodiment 51 or 52, wherein the sampleobtained from the subject is a plasma sample.

Embodiment 54: The method of embodiment 37, wherein the one or moremRNAs are selected from among miR-200a-3p, miR-1185-5p, miR-33a-5p,miR-574-3p, and miR-663b.

Embodiment 55: The method of embodiment 37, wherein the one or moremRNAs are each of miR-200a-3p, miR-1185-5p, miR-33a-5p, miR-574-3p, andmiR-663b.

Embodiment 56: The method of embodiment 54 or 55, wherein the sampleobtained from the subject is a plasma sample.

Embodiment 57: The method of embodiment 37, wherein the one or moremRNAs are selected from among miR-1185-5p, miR-33a-5p, miR-574-3p, andmiR-663b.

Embodiment 58: The method of embodiment 37, wherein the one or moremRNAs are each of miR-1185-5p, miR-33a-5p, miR-574-3p, and miR-663b.

Embodiment 59: The method of embodiment 57 or 58, wherein the sampleobtained from the subject is a plasma sample.

Embodiment 60: The method of embodiment 37, wherein said detectingcomprises measuring the expression of the one or more miRNAs bybarcode-based assay, miRNA microarray analysis (e.g., chip), digitalpolymerase chain reaction (PCR), real-time PCR, quantitative reversetranscription PCR (qRT-PCR), semi-quantitative PCR, Northern blot, or insitu hybridization.

Embodiment 61: The method of embodiment 37, wherein the subject is ahuman.

Embodiment 62: The method of embodiment 61, further comprisingadministering to the subject a therapy directed at preventing ortreating pancreatic cancer.

Embodiment 63: The method of embodiment 62, wherein the therapycomprises surgical resection or pancreatoduodenectomy (Whippleprocedure).

Embodiment 64: The method of embodiment 62 or 63, wherein the therapycomprises administration of an anti-cancer agent (e.g., achemotherapeutic or immunotherapy) to the subject.

Embodiment 65: The method of embodiment 37, wherein the referenceexpression level is that of:

-   -   a. an organism belonging to the same species as the subject        having no risk or a low risk of developing pancreatic cancer,    -   b. the subject when the subject had no risk or low risk of        developing pancreatic cancer, or    -   c. an organism belonging to the same species as the subject        having the pancreatic lesion and having no risk or low risk of        developing pancreatic cancer.

Embodiment 66: A kit for performing a barcode-based assay to quantifyexpression of miRNAs belonging to a profile of differentially expressedmiRNAs in a sample of an individual having high risk of developingpancreatic cancer, comprising vials containing different oligonucleotideprobes designed to quantify one or more miRNAs in a sample, wherein thedifferential expression of the one or more miRNAs, as compared to thereference expression level, is indicative of a higher risk of developingpancreatic cancer versus a lower risk of developing pancreatic cancer.

Embodiment 67: The kit of embodiment 66, wherein the barcode-based assaykit consists essentially of oligonucleotide probes designed to quantifyone or more of miR-100, miR-99b, miR-99a, miR-342-3p, miR-126, miR-888,miR-130a, let-7c, miR-150, miR-296, miR-199a, miR-199a-3p, and miR-302a,preferably, one or more of miR-100, miR-99b, miR-99a, miR-342-3p,miR-126, and miR-130a.

Embodiment 68: The kit of embodiment 66, wherein the barcode-based assaykit consists essentially of oligonucleotide probes designed to quantifyeach of miR-100, miR-99b, miR-99a, miR-342-3p, miR-126, miR-888,miR-130a, let-7c, miR-150, miR-296, miR-199a, miR-199a-3p, and miR-302a.

Embodiment 69: The kit of embodiment 66, wherein the barcode-based assaykit consists essentially of oligonucleotide probes designed to quantifyone or more of let-7a-5p, let-7d-5p, let-7f-5p, let-7g-5p, let-7i-5p,miR-107, miR-1260b, miR-126-3p, miR-142-3p, miR-145-5p, miR-146a-5p,miR-148a-3p, miR-15b-5p, miR-181a-5p, miR-191-5p, miR-199a-3p,miR-199b-3p, miR-20a-5p, miR-20b-5p, miR-22-3p, miR-23a-3p, miR-24-3p,miR-26a-5p, miR-27a-3p, miR-29c-3p, miR-335-5p, miR-337-5p, miR-340-5p,miR-423-5p, miR-4454, miR-593-3p, and miR-98.

Embodiment 70: The kit of embodiment 66, wherein the barcode-based assaykit consists essentially of oligonucleotide probes designed to quantifyeach of let-7a-5p, let-7d-5p, let-7f-5p, let-7g-5p, let-7i-5p, miR-107,miR-1260b, miR-126-3p, miR-142-3p, miR-145-5p, miR-146a-5p, miR-148a-3p,miR-15b-5p, miR-181a-5p, miR-191-5p, miR-199a-3p, miR-199b-3p,miR-20a-5p, miR-20b-5p, miR-22-3p, miR-23a-3p, miR-24-3p, miR-26a-5p,miR-27a-3p, miR-29c-3p, miR-335-5p, miR-337-5p, miR-340-5p, miR-423-5p,miR-4454, miR-593-3p, and miR-98.

Embodiment 71: The kit of embodiment 66, wherein the barcode-based assaykit consists essentially of oligonucleotide probes designed to quantifyone or more of miR-200a-3p, miR-1185-5p, miR-33a-5p, miR-574-3p, andmiR-663b.

Embodiment 72: The kit of embodiment 66, wherein the barcode-based assaykit consists essentially of oligonucleotide probes designed to quantifyeach of miR-200a-3p, miR-1185-5p, miR-33a-5p, miR-574-3p, and miR-663b.

Embodiment 73: The kit of embodiment 66, wherein the barcode-based assaykit consists essentially of oligonucleotide probes designed to quantifyone or more of miR-1185-5p, miR-33a-5p, miR-574-3p, and miR-663b.

Embodiment 74: The kit of embodiment 66, wherein the barcode-based assaykit consists essentially of oligonucleotide probes designed to quantifyeach of miR-1185-5p, miR-33a-5p, miR-574-3p, and miR-663b.

All patents, patent applications, provisional applications, andpublications referred to or cited herein are incorporated by referencein their entirety, including all figures and tables, to the extent theyare not inconsistent with the explicit teachings of this specification.

Following are examples that illustrate procedures for practicing theinvention. These examples should not be construed as limiting. Allpercentages are by weight and all solvent mixture proportions are byvolume unless otherwise noted.

Examples of certain embodiments of the invention include, but are notlimited to:

Materials and Methods for Example 1

Study population and biospecimens. A prospectively maintained clinicaldatabase was retrospectively reviewed to identify individuals whounderwent pancreatic resection for an IPMN between 1999 and 2011 atMoffitt Cancer Center and Research Institute (Moffitt) and had donatedtissue for research through protocols approved by the InstitutionalReview Board (IRB) of the University of South Florida. A pathologistwith expertise in PDAC and IPMN pathology (DC) used hematoxylin andeosin (H&E) stained slides from selected blocks to histologicallyconfirm the diagnosis and degree of dysplasia using World HealthOrganization (WHO) guidelines (22), and consulted with anotherpancreatic pathologist (BC) as needed. The final diagnosis representedthe most severe grade of dysplasia observed in the neoplastic epitheliumof each resected lesion, and multiple representative areas of thecorresponding grade were electronically marked on the H&Es. Examples ofgrades of IPMN dysplasia are shown in FIGS. 4A-4D.

Laser capture microdissection (LCM) and RNA isolation. Under RNAse-freeconditions, four 8-micron sections were cut from the FFPE blockcorresponding to each respective H&E. Sections were placed in a waterbath, mounted on uncharged and uncoated glass slides, air-driedovernight, and transferred to Moffitt's Analytic Microscopy Core forLCM. Sections were deparaffinized, hydrated, and stained usingnuclease-free Histogene solution (Applied Biosystems (ABI), Austin,Tex.), dehydrated, and then air-dried before placement in an Autopix LCMinstrument (Arcturus, Molecular Devices, Sunnyvale, Calif.). Locationsof dysplasia were verified using the marked electronic images. Cells ofinterest were captured from each section using Macro LCM Caps (ArcturusCapSure, #09F10A). Caps of cells from each case were pooled and 50 μL oflysis buffer was added to stop RNA degradation. Qiagen's miRNeasy™ FFPEIsolation Kit was used for total RNA isolation, which included isolationof small non-coding RNAs, according to the manufacturer's procedures.RNA quantity and quality was assessed by Optical Density (OD) at 260 and280 nm using a Nanodrop spectrophotometer. When RNA quantity wasinsufficient, additional tissue sections were processed. If RNA qualitywas poor, an ethanol precipitation was performed.

High throughput miRNA expression analysis. Genome-wide miRNA profilingwas conducted using Taqman® MicroRNA Arrays, also known as Taqman LowDensity Array (TLDA) ‘Pool A’ Card version 3.0. This 384-microfluidicarray was designed to perform quantitative reverse transcriptase(qRTPCR) reactions simultaneously (Applied Biosystems, Austin, Tex.,USA) on 378 mature miRNAs and 6 endogenous controls. Using 20 nanograms(ng) of total RNA as input, cDNA was synthesized with multiplexedMegaplex™ RT primers, preamplified with Megaplex™ PreAmp Primers, andmixed with TaqMan Universal PCR Master Mix (Applied Biosystems). Sampleswere loaded onto TLDA cards for expression analysis.

Individual qRT-PCR validation of miRNA candidates. The most deregulatedmiRNAs were evaluated in an independent set of 21 IPMNs (13 high-riskand 8 low-risk) as part of a replication phase. Total RNA was isolatedfrom microdissected cells, and singleplex qRT-PCR assays were performedusing 10 ng total RNA per reaction using pre-designed Taqman® MicroRNAAssays (Applied Biosystems, Foster City, Calif.). The expression levelof the most stable and abundantly expressed endogenous control was usedfor normalization. All assays were carried out in triplicate to ensurereproducibility. Positive and negative control (nuclease free water)samples were used to evaluate reagent performance and contamination. PCRwas run on the 7900HT instrument according to the manufacturer'sinstructions. For each sample, the threshold cycle (Ct) was calculatedby the ABI Sequence Detection software v2.3.

Statistical Analyses. Descriptive statistics were determined usingfrequencies and percent for categorical variables and means and standarddeviations (SD) for continuous variables. The distributions ofcovariates were compared across the low- versus high-risk IPMN groupsusing t-tests for continuous variables and Chi-squared or Fisher's exacttests for categorical variables, as appropriate. Relative miRNAexpression levels were calculated using a method similar to thecomparative Ct (2-ΔΔCT) method. Briefly, ΔCT was calculated for eachmiRNA so that each miRNA was first normalized to the most stablyexpressed endogenous control, RNU44 (i.e. ΔCT=CT−RNU44). Normalized CTvalues were further calculated as log 2[Max (ΔCT)−ΔCT].

Nonparametric tests (Wilcoxon rank sum tests) were performed to comparethe normalized expression levels between groups for each miRNA. Falsediscovery rates (FDR) adjusting for multiple comparisons were estimatedusing q-values. Correlations between expression of the most deregulatedmiRNAs and selected clinical and pathological factors were examinedusing Pearson correlations for continuous variables and ANOVA andlogistic regression for categorical variables. Multivariable regressionanalysis was conducted to identify miRNAs associated with high-risk IPMNstatus independent of selected variables. To assess the accuracy andclinical utility of candidate miRNAs in differentiating betweenhigh-risk and low-risk IPMNs, receiver operating characteristic (ROC)curves were constructed using ΔCT values, with pathological diagnosis asthe gold standard. Logistic regression models predicting risk statuswere fit using values from the discovery dataset, and ROC curves wereused to predict low versus high-risk IPMN status in the replicationdataset. p-value of <0.05 was used as the threshold for statisticallysignificance in most analyses. All statistical analyses were performedusing Matlab version 2009b and R version 2.13.1. To visualize miRNAexpression patterns, we generated heatmaps and performed unsupervised,hierarchical clustering using Matlab.

Bioinformatics Analyses. To gain insight into mechanisms responsible formiRNA-mediated progression to pancreatic malignancy, publicly-availabletools were used to identify genes and pathways controlled by thecandidate miRNAs. We first determined experimentally-verified miRNAtargets of the most deregulated miRNAs using the miRecords and TarBasedatabases and published literature. Using identified mRNAs ascandidates, a pathway enrichment analysis was conducted using GeneOntology's MetaCore database (see world wide website genego.com).Pathways related to PDAC and interaction hubs (genes with more than 5interactions) were identified and overlapped withexperimentally-verified targets to narrow down the number ofbiologically important genes.

Microarray gene expression analysis of IPMNs. Under an IRB-approvedprotocol, fresh-frozen tumor tissue from patients treated at Moffitt waspreviously arrayed on Affymetrix HuRSTA-2a520709 GeneChips (Affymetrix,Santa Clara, Calif.) which contained 60,000 probe sets representing˜25,037 unique genes (Affymetrix HuRSTA-2a520709, GEO: see world widewebsite: ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL10379). Of 14,492distinct solid tumors that were arrayed, twenty-three representedsurgically-resected, pathologically-confirmed IPMNs (17 invasive and 6non-invasive (1 LG, 1 MG, 4 HG)). For the 23 IPMNs that were arrayed,expression data for 21 candidate targets of interest (66 probe-sets)highlighted by bioinformatics analysis were normalized using RobustMulti-array Average (RMA) and then extracted. Due to small cell counts,the high-risk group represented all invasive IPMNs and was compared to alow-risk group that included all non-invasive IPMNs.

Nonparametric tests (rank sum tests) were used to compare expressionbetween groups for each target gene. FDRs were estimated using q-values.Of the 23 IPMN cases with microarray data, 8 were evaluated as part ofthe current miRNA discovery (n=2; 1 LG, 1 HG) or replication phase (n=6;1 MG, 3 HG, 2 invasive), which enabled preliminarily exploration ofrelationships between miRNA and target mRNA expression for pairedsamples using Pearson correlations.

Example 1—Identification of Tissue Mirnas Differentially Expressed inSubjects Having Pancreatic Cancer or Having High Risk of DevelopingPancreatic Cancer

A. Study Population

Forty-nine IPMN cases contributed tissue for the discovery (n=28; 19high-risk (all HG) and 9 low-risk (all LG)) or replication phase (n=21;13 high-risk (11 HG, 2 invasive) and 8 low risk (4 LG and 4 MG)). Selectclinical and pathologic characteristics of patients with IPMNs in thediscovery phase (N=28) is shown in Table 1A and clinical and pathologiccharacteristics of the patients in discovery and replication phase (17low-risk and 32 high-risk IPMN participants) are shown in Table 1B.Overall, characteristics were not significantly different between thehigh- and low-risk groups (Table 1B). Age at diagnosis was slightlyolder in individuals with high-risk IPMNs (69.1 years) compared to thosewith low-risk IPMNs (65.1 years). The predominant tumor location for 59%of the high-risk IPMNs was the pancreatic head, whereas most (65%)low-risk IPMNs occurred in the pancreatic body or tail. On endoscopicultrasound (EUS), signs of malignant potential were observed morefrequently among high-risk (72%) compared to low-risk IPMNs (47%)(P=0.09). Only 40% of high-risk IPMNs were observed to be >3 cm on EUS.High-risk IPMNs were significantly more likely to involve the mainpancreatic duct upon pathological review compared to low-risk IPMNs(p=0.0007). The distribution of characteristics was similar among casesin each phase.

TABLE 1A Select Clinical and Pathologic Characteristics of Patients withIPMNs (N = 28) in discovery phase. Low- High- All grade grade IPMNs (n =9) (n = 19) (N = 28) Age at diagnosis, mean (yrs) 66.4 68.4 67.8 GenderMale 5 (56) 10 (53) 15 (54) Race White, Non-Hispanic 8 (89) 18 (95) 26(93) Predominant tumor location in pancreas Head 4 (44) 14 (74) 18 (64)Body or Tail 5 (56) 5 (26) 10 (36) Signs of malignant potential¹ on EUS5 (56) 15 (79) 20 (71) Pancreatic duct involvement² Main duct 1 (11) 7(37) 8 (29) Side branch duct 4 (44) 2 (11) 6 (21) Mixed 3 (33) 9 (47) 12(43) Size of largest cyst <3 cm. 7 (78) 10 (53) 17 (61) >3 cm. 2 (22) 9(47) 11 (39) Size of largest cyst², mean (SD) (cm) 2.3 (1.5)  2.7 (1.3)2.4 (1.1) Asymptomatic Yes 2 (22) 2 (11) 4 (14) No 7 (78) 17 (89) 24(86) Ever Smoker Yes 8 (89) 11 (58) 19 (68) No 1 (11) 8 (42) 9 (32) Datarepresent counts (percentages) unless otherwise indicated. Counts maynot add up to the total due to missing values, and percentages may notequal 100 due to rounding. ¹Signs of malignant potential on endoscopicultrasound (EUS) included main duct involvement, main duct dilation (>6mm), presence of mural nodules, septation, wall thickness, or cystsize >3 cm. ²Based on pathology report.

TABLE 1B Clinical and Pathologic Characteristics of Patients with IPMNs(N = 49) in discovery and replication phase. Low-risk¹ High-risk² IPMNsIPMNs Variable (n = 17) (n = 32) P-value³ Age at diagnosis, mean (SD)65.1 (9.6) 69.1 (9.7) 0.18 (yrs) Gender Male 11 (65) 18 (56) 0.57 Female6 (35) 14 (44) Race White, Non-Hispanic 15 (88) 29 (91) 0.79 Other 2(12) 3 (9) Year of Surgery 1999-2005 1 (6) 5 (16) 0.32 2006-2011 16 (94)27 (84) Predominant tumor location Pancreatic Head 6 (35) 19 (59) 0.11Pancreatic Body or Tail 11 (65) 13 (41) Signs of malignant potential ⁴ 8(47) 23 (72) 0.09 on EUS Size of largest cyst on EUS ⁴ <3 cm. 14 (82) 18(60) 0.11 ≥3 cm. 3 (18) 12 (40) Size of largest cyst ⁴, mean (SD) 2.0(1.2) 2.5 (1.3) 0.21 (cm) Pancreatic duct involvement ⁵ Main duct ormixed 5 (29) 25 (78) 7 × 10 ⁻⁴ Side branch duct 9 (53) 4 (13)Asymptomatic Yes 3 (18) 4 (13) 0.62 No 14 (82) 28 (88) Personal historyof chronic pancreatitis Yes 6 (35) 16 (50) 0.32 No 11 (65) 16 (50)Family history of pancreatic cancer Yes 1 (6) 2 (6) 0.97 No 15 (88) 29(91) Ever Smoker Yes 11 (65) 20 (63) 0.88 No 6 (35) 12 (38) Datarepresent counts (percentages) unless otherwise indicated. Counts maynot add up to the total due to missing values, and percentages may notequal 100 due to rounding. ¹Low-risk IPMNs are represented by 12low-grade and 5 moderate-grade IPMNs. ²High-risk IPMNs are representedby 30 high-grade and 2 invasive IPMNs. ³P-value for differences betweenlow- and high-risk groups using chi-squared or Fisher's exact tests andt-tests for categorical and continuous variables, respectively. Valuesin bold are statistically significant (P < 0.05). ⁴ Signs of malignantpotential on endoscopic ultrasound (EUS) include main duct (MD)involvement, MD dilation (>5 mm), mural nodules, septation, wallthickness, or cyst size >3 cm. ⁵ Based on pathological reviewpost-resection.

B. Biospecimen Quality

Surgically-resected tissue was pathologically evaluated for 58 uniqueIPMNs. Tissue was not profiled for 6 cases due to an inconclusive gradeof dysplasia (n=1), sparse regions of dysplasia (n=2), or technicalissues during LCM (n=3). Representative examples of pre- andpost-microdissection images of low- and high-grade IPMNs are shown inFIGS. 1A and 1B, respectively. The average total number of cellscaptured per case was 8,498 (range: 780-65,956), and the average totalRNA recovery was 139 ng (range: 48-591 ng). The quality of RNA wasappropriate for most cases as evidenced by optical density 260/280readings in the range of 1.8-2.0. Sub-optimal RNA quantity or qualitywas observed for 3 cases, leaving 49 cases with adequate tissue formiRNA expression analyses.

C. miRNA Expression Analysis in the Discovery and Replication Phase

In the discovery phase, 236 of 378 miRNAs evaluated (62.4%) weredetectable in at least half of the 28 samples evaluated and wereincluded in subsequent analyses. This percentage is comparable to otherstudies (28). Thirty-five miRNA probes were significantly deregulated inhigh-risk compared to low-risk IPMNs (rank sum P<0.05, Table 2). The topderegulated miRNAs separated most low-risk from high-risk IPMNs as shownin the heatmap (FIG. 2A), though outliers existed, consistent with otherstudies (29). Several outliers may be explained by focal areas ofdysplasia available for sampling and/or inter-sample heterogeneity.

TABLE 2 The top 35 most differentially expressed miRNAs between high-risk (N = 19) and low-risk IPMNs (N = 9). mean median P-value FalseN^(a) N^(a) fold- fold- rank-sum discovery High- Low- miRNA probe changechange test rate risk risk hsa-miR-100-000437 4.90 5.86 0.0016 0.0929 199 hsa-miR-99a-000435 4.66 4.77 0.0027 0.0929 19 9 hsa-miR-99b-0004363.75 4.74 0.0027 0.0929 19 9 hsa-miR-126-002228 6.73 3.09 0.0037 0.092919 9 hsa-miR-342-3p-002260 3.34 4.85 0.0037 0.0929 19 9hsa-miR-888-002212 69.52 63.47 0.0057 0.0929 14 6 hsa-miR-130a-0004545.01 4.72 0.0059 0.0929 19 9 hsa-let-7c-000379 3.59 2.66 0.0059 0.092918 9 hsa-miR-150-000473 3.49 2.78 0.0081 0.0929 18 9 hsa-miR-199a-0004984.42 3.14 0.0081 0.0929 18 9 hsa-miR-199a-3p-002304 3.77 4.78 0.00810.0929 18 9 hsa-miR-296-000527 3.69 5.29 0.0081 0.0929 18 9hsa-miR-302a-000529 36.30 6.42 0.0094 0.0995 12 5 hsa-miR-125b-0004494.59 5.14 0.0113 0.1114 17 9 hsa-miR-218-000521 6.84 7.56 0.0131 0.120816 8 hsa-miR-424-000604 3.72 2.51 0.0156 0.1343 16 8 hsa-miR-411-0016103.70 4.31 0.0168 0.1361 18 9 hsa-miR-523-002386 5.09 3.15 0.0196 0.150315 4 hsa-miR-376a-000565 3.41 6.76 0.0208 0.1509 19 9 hsa-miR-381-0005714.35 6.96 0.0240 0.1535 19 8 hsa-miR-494-002365 3.57 3.36 0.0268 0.153511 7 hsa-miR-133a-002246 4.66 8.79 0.0269 0.1535 19 9hsa-miR-139-5p-002289 3.37 4.63 0.0269 0.1535 19 9 hsa-miR-149-0022558.29 12.69 0.0276 0.1535 11 9 hsa-miR-146b-3p-002361 11.48 22.42 0.02800.1535 10 5 hsa-miR-193a-5p-002281 2.25 1.85 0.0289 0.1535 17 8hsa-miR-410-001274 3.12 3.98 0.0311 0.1589 17 9 hsa-miR-214-002306 3.965.68 0.0338 0.1637 16 9 hsa-miR-152-000475 2.15 3.12 0.0344 0.1637 19 9hsa-miR-142-3p-000464 4.25 3.31 0.0368 0.1693 18 7 hsa-miR-30c-0004192.73 3.27 0.0388 0.1728 19 9 mmu-miR-153-001191 0.09 0.05 0.0415 0.178912 6 hsa-miR-502-001109 4.63 7.01 0.0490 0.1936 15 8 hsa-miR-138-0022843.70 3.96 0.0491 0.1936 19 9 hsa-miR-204-000508 6.44 9.55 0.0491 0.193619 9 ^(a)Number of IPMNs in which the miRNA was detectable.

Using a FDR of 10%, 13 of the 35 miRNAs (miR-100, miR-99b, miR-99a,miR-342-3p, miR-126, miR-888, miR-130a, let-7c, miR-150, miR-296,miR-199a, miR-199a-3p, and miR-302a) were significantly deregulatedbetween the groups (Table 2). Of these 13 miRNAs, the top 6 (miR-100,miR-99b, miR-99a, miR-342-3p, miR-126, miR-130a) were selected forfurther evaluation based on their statistical significance, evidence tosupport their biological role in pancreatic carcinogenesis, and the factthat they were detectable in all evaluated samples. Expression levels ofeach of these 6 miRNAs were down-regulated in most high- versus low-riskIPMNs (Table 3). Unsupervised hierarchical clustering analysis alsoillustrated reduced expression for these 6 miRNAs in the high-riskcompared to the low-risk group (FIG. 2B). Experimentally-validated genetargets of the 6 miRNAs are listed in Table 3, and include well-knownoncogenes.

TABLE 3 Select candidate miRNAs differentially expressed in high- (N =19) vs. low-risk (N = 9) IPMN tissue. Median Mean Fold FoldExperimentally validated miRNA P-value¹ change² change² gene target(s)³miR-100 1.6 × 10⁻³ 5.9 4.9 ATM, FGFR3, IGF1R, MMP13, mTOR, PLK1, RPTORmiR-99b 2.7 × 10⁻³ 4.7 3.7 RAVER2 miR-99a 2.7 × 10⁻³ 4.8 4.7 AGO2, COX2,FGFR3, IGF1R, MEF2D, mTOR, RAVER2, RPTOR, SERPINE1, SKI, TRIB1miR-342-3p 3.7 × 10⁻³ 4.8 3.3 BMP7, DNMT1, GEMIN4 miR-126 3.7 × 10⁻³ 3.16.7 ADAM9, CCNE2, CRH, CRK, CRKL, DNMT1, EGFL7, KRAS, HOXA9, IRS1, PGF,PIK3R2, PLK2, PTPN7, RGS3, SLC45A3, SOX2, SPRED1, TOM1, TWF2, VCAM1,VEGFA miR-130a 5.9 × 10⁻³ 4.7 5.0 APP, ATG2B, ATXN1, CSF1, DICER1, ESR1,HOXA10, HOXA5, KLF4, MAFB, MEOX2, PPARG, RUNX3, TAC1, TP53INP1 ¹Wilcoxonrank-sum test. ²All fold-changes represent decreased expression in thehigh-risk group (all high-grade IPMNs) versus the low-risk group (alllow-grade IPMNs). ³According to data in Tarbase(diana.cslab.ece.ntua.gr/tarbase/), miRecords (mirecords.biolead.org/),or other sources.

In the replication phase, expression of miR-100, miR-99b, miR-99a,miR-342-3p, miR-126, and miR-130a was evaluated in 21 independent IPMNs(13 high-risk and 8 low-risk) (FIG. 5). The same trends in expression asin the discovery phase were observed with the expression levels of eachmiRNA down-regulated in high-risk compared to low risk IPMNs (FIGS. 6Aand 6B). Using a threshold of p<0.05, results reached marginalstatistical significance, possibly due to the small sample size. Amongthe 6 miRNAs evaluated, miR-130a was most strongly associated withhigh-risk IPMN status (2.9 median fold change between the high- andlow-risk group, p=0.065), followed by miR-99b (2.7 median fold change,p=0.103) and miR-100 and miR-342-3p (2.2 median fold-change, p=0.119).Most clinical and pathological factors were not correlated with miRNAexpression level in the discovery phase (Table 4). However, anassociation was observed between low miR-99b expression and main ductinvolvement (P=0.021), a variable independently associated withhigh-risk IPMN status (P=0.044). After including both miR-99b expressionlevel and main duct involvement in multivariate regression models, lowmiR-99b expression was marginally associated with high-risk IPMN status(P=0.051). Serum albumin levels were positively correlated with miR-99a(r=0.52, P=0.004) and miR-100 expression (r=0.49, P=0.008).

The expression level of several miRNAs (miR-99a, miR-99b, miR-100) washighly correlated (0.79<r<0.97), which may be expected since they arefrom the same miRNA family (Table 4). No factors were associated withmiRNA expression (P<0.05) in the replication phase.

TABLE 4 Correlations between candidate miRNA expression level andselected continuous clinical and pathologic characteristics miR_100miR_99b miR_99a miR_342_3p miR_126 miR_130a N r P r P r P r P r P r PAge at diagnosis (years) 28 −0.14 0.47 −0.02 0.93 −0.16 0.42 0.19 0.34−0.25 0.2 −0.18 0.37 Size of the Largest Cyst (cm) 28 −0.1 0.63 −0.150.45 −0.21 0.28 −0.24 0.21 −0.2 0.32 −0.19 0.34 Size of the MainPancreatic 15 −0.48 0.07 −0.49 0.07 −0.33 0.23 −0.17 0.55 −0.13 0.65−0.49 0.07 Duct (mm) Fluid CEA levels (ng/uL) 16 −0.24 0.36 −0.16 0.56−0.13 0.62 −0.08 0.77 −0.42 0.11 −0.33 0.22 Serum glucose levels (mg/dL)27 −0.17 0.4 −0.19 0.34 −0.18 0.38 −0.29 0.14 0.19 0.33 −0.05 0.79 Serumamylase level (u/L) 10 0.4 0.25 0.24 0.5 0.214 0.55 0.44 0.2 0.54 0.11−0.17 0.65 Serum CA19-9 level (U/ml) 21 0.04 0.86 0.18 0.44 −0.16 0.49−0.08 0.74 −0.02 0.95 0.026 0.91 Serum CEA level (ng/mL) 7 0.32 0.490.02 0.96 0.3 0.51 0.31 0.5 0.46 0.3 0.468 0.29 Serum albumin level(g/dL) 28 0.49 0.01 0.31 0.11 0.524 0 0.37 0.05 0.09 0.67 0.253 0.19Serum bilirubin level (mg/dL) 28 0.1 0.62 0.09 0.66 0.014 0.95 0.1 0.610.09 0.66 −0 0.99 Serum alkaline phosphatase 28 0.17 0.39 0.1 0.63 0.080.69 0.14 0.49 0.1 0.61 0.081 0.68 level (u/L) Body mass index (BMI)(kg/m²) 27 −0.11 0.6 −0.15 0.45 −0.1 0.64 0.01 0.96 0.16 0.43 0.044 0.83Pack Years Smoked 18 0.5 0.03 0.48 0.05 0.434 0.07 0.38 0.12 0.03 0.910.197 0.43 miR-100 28 1 NA 0.82 0 0.969 0 0.7 0 0.43 0.02 0.864 0miR-99b 28 0.82 0 1 NA 0.795 0 0.72 0 0.29 0.13 0.82 0 miR-99a 28 0.97 00.8 0 1 NA 0.72 0 0.44 0.02 0.858 0 miR-342_3p 28 0.7 0 0.72 0 0.715 0 1NA 0.22 0.25 0.593 0 miR-126 28 0.43 0.02 0.29 0.13 0.443 0.02 0.22 0.251 NA 0.569 0 miR-130a 28 0.86 0 0.82 0 0.858 0 0.59 0 0.57 0 1 NA r =Pearson correlation

Receiver operating characteristic (ROC) curves were constructed based onthe expression of miR-100, miR-99b, miR-99a, miR-342-3p, miR-126, andmiR-130a. Most areas underneath the curve (AUC) values were comparablefor the six individual miRNAs, with expression of miR-99a yielding thehighest AUC value of 0.87 in classifying between high- and low-riskIPMNs in the discovery phase (FIG. 7A). When using a signatureconsisting of three miRNAs (miR-99b, miR-130a, and miR-342-3p) from thediscovery model to predict high-risk IPMN status in the replication set,the AUC was 0.74 (95% CI:0.51-0.97) (FIG. 3). A model combiningexpression of miR-99b, miR-130a, and miR-342-3p with presence of mainduct involvement enabled slightly higher utility in discriminatingbetween groups (AUC=0.81).

D. Follow-Up with Bioinformatics Analyses and Gene Expression Profiling

Gene ontology pathway enrichment network analysis revealed severalimportant interaction hubs, including ESR1, PPARG, VEGF-A, mTOR, IRS-1,and SOX2 (FIG. 8). The top four most marked gene ontology maps that wereidentified contribute to tumor progression through interactions withhistone deacetylase and calcium/calmodulin-dependent kinases, hypoxiainducible factor regulation, growth factors signaling, and cytoskeletonremodeling (Table 5). This analysis also confirmed that identifiedtarget genes were associated with pancreatic diseases (2.2×10⁻³⁰) andpancreatic neoplasms (7.6×10⁻²⁹).

TABLE 5 Gene ontology categories of biological pathways overrepresentedby miRNA-mediated changes in target gene expression that maydifferentiate between high- and low-risk IPMNs. False Discovery PathwayP-value Rate (FDR) Developmental role of histone deacetylase 9.5 × 10⁻⁸2.4 × 10⁻⁵ (HDAC) and calcium/calmodulin-depdendent kinase (CaMK)Transcription receptor-mediated hypoxia 5.9 × 10⁻⁷ 7.5 × 10⁻⁵ induciblefactor (HIF) regulation Developmental membrane-bound ESR1: 1.3 × 10⁻⁶1.0 × 10⁻⁴ interaction with growth factors signaling Cytoskeletonremodeling with TGF and WNT 6.9 × 10⁻⁶ 3.8 × 10⁻⁴ DNA damage with BRCA1as a transcription 7.5 × 10⁻⁷ 3.8 × 10⁻⁴ regulator Signaltransduction-AKT signaling 3.3 × 10⁻⁵ 8.9 × 10⁻⁴ Development: VEGFsignaling and activation 3.3 × 10⁻⁵ 8.9 × 10⁻⁴ Development:ligand-independent activation 3.9 × 10⁻⁵ 8.9 × 10⁻⁴ of ESR1 and ESR2Role of alpha-6/beta-4 integrins in carcinoma 3.9 × 10⁻⁵ 8.9 × 10⁻⁴progression

Gene expression was significantly up-regulated in 17 high-risk versus 6low-risk IPMNs for DNMT1, ATG2B, MEOX2, and IRS1 (p<0.10 and FDR<0.30).Correlations between miRNA and mRNA expression were evident in 2miRNA-mRNA pairs, miR-342-3p: DNMT1 (r=0.81, p=0.05) and miR-126: IRS1(r=0.78, p=0.07). No statistically significant inverse correlationsbetween miRNAs and their target genes were observed.

miRNA expression analysis of IPMNs that was followed by both areplication and a functional follow-up phase, biologically meaningfulmiRNAs that help distinguish between high- and low-risk IPMNs werediscovered. Six miRNAs (miR-100, miR-99b, miR-99a, miR-342-3p, miR-126,and miR-130a) were under-expressed in high-risk compared to low-riskIPMNs in the discovery and replication phase, suggesting that low orreduced levels of these miRNAs (and possibly increased levels of targetgenes they regulate) may be associated with progression to invasion.Moreover, ROC analysis suggested that a combination of these miRNAs mayaccurately classify IPMNs based on histologic severity (FIG. 3).

The identified miRNAs can have a role as tumor suppressors andregulators of oncogenes that contribute to cell proliferation andinvasion in pancreatic and other malignancies (Table 3)(30-37). Forexample, an experimentally-validated target of miR-100 is polo-likekinase 1 (PLK1), a regulator of proliferative activity overexpressed inearly PDAC (36) that represents a novel target for chemoprevention andtherapeutic strategies (36, 38). Also noteworthy, miR-342-3p can inhibitcancer cell proliferation and invasion by directly targeting DNAmethyltransferase 1 (DNMT1), a gene that maintains DNA methylation (35).DNMT1 mRNA expression has been correlated with PDAC progression; thosewith higher DNMT1 tissue expression had poorer survival than those withlower expression (37). Loss of another candidate, miR-126, has beenassociated with PDAC progression by targeting oncogenes such as KRAS(31, 32) and insulin receptor substrate-1 (IRS-1), a mediator ofphosphoinositide 3-kinase (PI3K) activation in quiescent PDAC cells(39).

Pathway enrichment network analysis underscored that these and othermiRNA-mediated mechanisms may explain how IPMNs progress to invasivedisease (Table 5). Even though miRNAs are generally believed to regulateexpression at the protein level (15), we postulated that measuring mRNAexpression may be useful for determining how transcriptional machinerydiffers between a pre-malignant and a malignant IPMN state.

Consistent with our predictions, mRNA targets of miR-130a (ATG2B andMEOX2), miR-342-3p (DNMT1), and miR-126 (IRS-1) were up-regulated inhigh-risk versus low-risk IPMNs. Other miRNA targets may not havedemonstrated noticeable mRNA level changes since a strong correlationbetween mRNA and protein abundance may not exist (40). We also exploredcorrelations between miRNA and mRNA expression in the reduced set ofIPMNs with both data types. Although positive correlations were observedin 2 miRNA-mRNA pairs (miR-342-3p:DNMT1 (r=0.81, p=0.05) and miR-126:IRS1 (r=0.78, p=0.07)), no statistically significant inversemiRNA:target gene correlations were observed. Indeed, previous studiesobserved more positively correlated than negatively correlatedinteractions (41), supporting a positive regulatory role of miRNAs (42).Due to the modest sample size of IPMNs evaluated, caution should betaken when interpreting these mRNA-based findings. Tissue microarraysare being constructed on a larger series of IPMNs so that proteinexpression can be evaluated.

Matthaei et al. (28) and Lubezky et al. (29) also conducted genome-widemiRNA profiling (Table 6). Matthaei et al. (28) evaluated miRNAexpression in 22 IPMN tissue and 7 pancreatic cyst fluid (CF) samples,and performed validation using 23 additional IPMN FFPE samples and CFsamples. miR-342-3p and miR-99b were among the miRNAs thatdifferentiated between high- and low-risk groups using FFPE tissue (andCF) (28), demonstrating consistency of findings across our two studiesand providing a form of external validation. No overlap existed betweenfindings observed by Lubezky et al. (29) and the current study (Table6).

TABLE 6 Studies of tissue-based miRNA expression in surgically-resectedIPMNs. Habbe ²⁶ Matthaei ²⁸ Park ⁴³ Lubezky ²⁹ Caponi ⁴⁴ CurrentInvention Discovery phase N IPMNs^(a) 15 22  2 30 81 28 (non-inv) (10LG, 12 HG^(b)) (1 LG, 1 HG) (10 LG, 5 MG, (16 non-inv, (9 LG, 19 HG) 5HG, 10 inv) 65 inv) Platform Taqman Taqman cDNA- Gene Chip Taqman TaqmanSingleplex MiRNA Array/ mediated miRNA Array Singleplex MiRNA Array/qRT-PCR qRT- PCR ligation qRT-PCR qRT-PCR N miRNAs   12 ^(c) 750  NA850   3 ^(d) 378  evaluated (RNU6B^(e)) (‘diffpairs’) (Robust multi-(RNU6^(e)) (RNU44^(e)) (normalization chip array method) algorithm)Replication phase^(f) N IPMNs 64 23 20 18 None 21 (13 LG, 31 MG, (3 LG,9 HG, (NA) (9 LG, 9 inv) (4 LG, 4 MG, 20 HG) 11 inv) 11 HG, 2 inv)Platform LNA-ISH qRT-PCR qRT-PCR qRT-PCR NA qRT-PCR (N miRNAs (2)(26^(f)) (NA) (4) (6) evaluated) Most miR-21, -155 miR-24, -18a,miR-552, -25, miR-217, -21, miR-21, -155 miR-100, -99b, deregulated-30a-3p, -92a, -182, -1300, -708, -155 -99a, -342-3p, miRNAs in high--106b, -342-3p -183 -196a, -30c -126, -130a versus low-risk -99b,-142-3p, IPMNs ^(g) -532-3p Abbreviations: IPMN = intraductal papillarymucinous neoplasm; inv = invasive; LG = low-grade; MG = moderate-grade;HG = high-grade; LNA-ISH = locked nucleic acid-in situ hybridization; NA= not available. ^(a)Some studies also evaluated normal pancreas tissue,PDAC tissue, and/or biofluids (pancreatic cyst fluid or pancreaticjuice). ^(b)7 of the 12 HG IPMNs had associated invasive disease. ^(c)The 12 evaluated miRNAs include: miR-15a, -16, 17-5p, -21, -100, -107,-155, -181a, -181c, -210, -221, -223. ^(d) The 3 miRNAs that wereevaluated include: miR-21, -155, -101. ^(e)Endogenous control^(f)Represents the number of independent IPMNs in addition to thoseprofiled in the discovery phase. ^(g) miRNAs appearing in bold font werehighlighted in more than one investigation. The 9 miRNAs highlighted byMatthaei et al. are represented in their final predictive model whichwas also based on cyst fluid analysis.

Since factors differed between studies (study populationcharacteristics, sample preparation procedures, the platform used(qRT-PCR versus microarray), normalization approaches, etc.), it is notsurprising that different miRNAs were characteristic of high-risk IPMNstatus (Table 6). Although the sample sizes of our discovery andreplication phases were relatively modest, they were comparable or evenlarger than other studies with regard to the number of high-grade caseswithout associated invasion that were evaluated. This is important froma clinical standpoint because it would be opportune for the medical teamto have a diagnostic adjunct that could reliably detect high-gradedysplasia so that intervention could occur prior to invasion. Also ofclinical importance, we observed that low miR-99b expression wasassociated with main duct involvement, a marker of histologicprogression that was not observed pre-operatively by imaging for six HGcases in our study.

We also observed positive correlations between serum albumin levels andexpression of miR-99a and miR-100, findings in line with data suggestingthat high serum albumin is correlated with better survival in PDACpatients (45) (and with low-grade disease in our study). This infersthat it may be helpful to monitor serum albumin levels in patients withIPMNs. Larger prospective studies are needed to validate theseobservations.

Additional strengths of our study include the well-annotated tissue andsound methodologic approach which capitalized upon confirmatorypathological review, standardized procedures for microdissection and RNAisolation of multiple representative regions per case, an establishedplatform for miRNA profiling, and our functional follow-up usingbioinformatics tools and available microarray data. Internal validity ofour findings is evidenced by high correlations between expression levelsof miRNAs from the same family within and between samples. Onelimitation was the fact that we evaluated resected tissue. Some of thesecysts (those deemed to be low- or moderate grade upon pathologic review)would not have been removed if tools were available to have properlydiagnosed them pre-operatively.

Taken together, the new miRNAs identified here (e.g., miR-99a, miR-100,miR-126, miR-130a) and the miRNAs that have also been highlighted byother tissue-based studies of IPMNs (e.g., miR-99b, -342-3p) warrantconsideration as biomarkers. Moreover, given that miRNAs are releasedfrom tissues into circulation in a stable form protected from endogenousRNAse activity (46) and preliminary data support the clinical utility ofmiRNAs circulating in pancreatic juice or aspirate (20, 47), cyst fluid(28), and serum (48), there is great potential for a minimally-invasivemiRNA-based assay to be used in the clinic to classify newly-diagnosedpancreatic cysts based on their malignant potential. Such an assayshould be evaluated in conjunction with clinical and pathologic factorsand emerging analytes and genetic markers (49, 50) to increasesensitivity and specificity.

Furthermore, functional evaluation of the biological processes in whichthe emerging miRNAs and their target genes are involved may aid inunderstanding the molecular underpinnings of progression to pancreaticmalignancy so that novel prevention and early detection strategies canbe developed. In conclusion, a miRNA signature has the potential toserve as a promising diagnostic adjunct for directing management ofnewly-diagnosed IPMNs toward watchful waiting or resection. Thisinvestigation provides novel biological insights into progression topancreatic malignancy, and has potential to advance this field closer tosolving this clinical challenge.

Materials and Methods for Example 2

Study population and biospecimens. A prospectively maintained clinicaldatabase was retrospectively reviewed to identify individuals whounderwent a pancreatic resection for an IPMN between 2006 and 2011 at H.Lee Moffitt Cancer Center and Research Institute (Moffitt) and hadprovided written consent for blood to be donated pre-operatively forresearch through several protocols approved by the Institutional ReviewBoard (IRB) of the University of South Florida, including Total CancerCare (see moffitt.org website) (27). IRB approval was also specificallygranted for the research described herein (IRB #Pro4971). The diagnosisand degree of dysplasia was histologically confirmed using World HealthOrganization (WHO) guidelines (22). The final diagnosis represented themost severe grade of dysplasia observed in the neoplastic epithelium ofeach resected lesion. None of the cases received pre-operativechemotherapy or radiation. Age- and gender-matched healthy controls withno current or prior history of pancreatic disease or symptoms whopresented to Moffitt's

Cancer Screening and Prevention Center during the same time period anddonated blood through a related IRB-approved protocol using the sameprocedures were also eligible for inclusion.

Blood was collected from consented participants via phlebotomy in a 7 mLEDTA tube and processed for plasma within two hours using standardprocedures (60). The EDTA tube was inverted 3 times and spun at 3600 rpmfor 8 minutes and then plasma was aliquoted into 0.5 mL bar-codedcryovials and banked at −80° C. Demographic, clinical, and epidemiologicdata from all subjects was collected from an electronic questionnaire,the medical record, Moffitt's cancer registry, and other source systems.

RNA isolation from plasma and quality control. While using precautionsto prevent RNAse contamination and RNA degradation, one 0.5 mL cryovialof plasma was retrieved and thawed from each subject. To control forvariance in the starting material and the efficiency of the downstreamtotal RNA extraction step, RNA spike-in miRNAs (synthetic controltemplates) were used according to manufacturer protocols and publishedrecommendations (61). Total RNA isolation that includes small RNAs wasperformed on 500 uL of plasma using the Plasma/Serum Circulating andExosomal RNA Purification Mini Kit (Slurry Format) from Norgen Biotek(Ontario, Canada) according to manufacturer protocols. This kit waschosen due to its ability to isolate total RNA of pure quality and amplequantity from plasma (62). After adding lysis buffer to the plasmasamples, 1000 attomoles of the synthetic RNA oligonucleotides (spike-inoligos) osa-miR-414, cel-mi-248, and ath-miR-159a (Operon, Inc,Huntsville, Ala.) were added. No-template control samples were run tomonitor the baseline for the spike-ins. RNA was eluted in 100 μL water,concentrated to 20 μl using Amicon Ultra 0.5 mL centrifugal filters witha 3 KDa molecular weight cut-off (Sigma-Alrich, St. Louis, Mo.), and 3μL was used for each NanoString assay.

Total RNA concentration and integrity were assessed using the NanoDropspectrophotometer (NanoDrop Technologies, Waltham, Mass.) and an AgilentBioanalyzer (Agilent, Santa Clara, Calif.), respectively. Sincehemolysis (rupturing of erythrocytes) can be a source of variation instudies of circulating miRNAs, a multi-pronged approach was used toassess the possibility of hemolysis based on recommended guidelines(63-65): a) prior to RNA extraction, samples were visually inspected fora pink/red hue, b) oxygen hemoglobin absorbance of isolated RNA wasmeasured at λ=414 nm, with values exceeding 0.2 indicative of hemolysis,and c) signal levels were evaluated post-hoc for cellular miRNAs likelyto be elevated in the presence of hemolysis (i.e., miR-451, miR-16).

High-throughput measurement of miRNA abundance. The NCOUNTER™ Human v2miRNA Expression Assay Codeset (Nanostring Technologies, Seattle, Wash.,USA) was used to simultaneously quantify the abundance of 800 humanmiRNAs. The Codeset also includes two types of built-in controls:positive controls (spiked RNA at various concentrations to assessoverall assay performance, n=6) and negative controls (alien probes forbackground calculation, n=8). The NCOUNTER™ platform was selectedbecause of its greater sensitivity and precision than microarrays andTaqman-based qRT-PCR (66). Additionally, since RNA isolated from plasmacontains inhibitors of the reverse transcriptase and Taq polymeraseenzymes used in qPCR, Nanostring's technology has an advantage overPCR-based methods in that reverse transcription and amplification stepsthat may introduce bias are not required (59). This platform involvesdirect digital measurement of miRNA abundance using color-coded probepairs which contain a reporter probe (to carry a fluorescent signal) anda capture probe (to immobilize the complex for data collection) (59).Using 3 μL of the extracted plasma RNA as input, preparation involvedmultiplexed ligation of DNA sequences called miRtags to the maturemiRNAs through sequence-specific oligonucleotide bridges in a singletube by controlling annealing and ligation temperatures. Excess tags andbridges were removed via an enzymatic step, and the tagged mature miRNAprobes were hybridized to a color-coded reporter probe pair for datacollection. Reporter probes were counted for each miRNA using theNCOUNTER Digital Analyzer at a setting of 555 fields of view (FOV).

Data Processing and Quality Control. For each sample,background-corrected measures of miRNA expression were estimated bysubtracting the negative control average plus two standard deviation(SD) cut-point from the raw miRNA counts. miRNAs with less than 20% ofsamples above the negative control cut-point (i.e., low-expressionprobes) were removed from downstream analysis, leaving only those miRNAswith substantial counts above background. Human messenger RNA (mRNA)housekeeping genes included in the codeset (ACTB, B2M, GAPDH, RPL19 andRPLP0) were used to evaluate possible sample contamination. To accountfor variances in the starting material and RNA extraction efficiency,data for each sample was normalized using the geometric mean of the 3spike-in oligos. Biological normalization was then performed using thefour most stable/invariant circulating miRNAs as endogenous controls,similar to other studies (67,68). Any of the four miRNAs that were knownto cross-hybridize with the spike-ins or known to be affected byhemolysis were replaced with the next most stable/invariant circulatingmiRNA. Normalized data was log 2-transformed prior to signatureselection.

Statistical Analysis. Descriptive statistics were determined usingfrequencies and percents for categorical variables and means andstandard deviations (SD) for continuous variables.

Identification of a plasma miRNA signature to differentiate between IPMNcases and controls: To identify miRNAs that differentiate between IPMNcases and non-diseased controls, we used linear models for microarraydata (LIMMA) (69), a Bayesian t-test that accounts for multiplecomparisons. miRNAs with false discovery rates (FDR)<15% were includedin the signature. Principal component analysis (PCA) was then used toefficiently reduce the data dimension into a small set of uncorrelatedprincipal components presumably linked to biological effects and togenerate an overall ‘IPMN-risk score’ to represent the overall combinedeffect of the IPMN-risk miRNA signature. To represent the overallexpression level for the signature, we used the first principalcomponent (PC1, a weighted average of expression among the identifiedmiRNAs), as it accounts for the largest variability in the data. Thatis, IPMN-risk score=Σw_(i)x_(i), a weighted average expression among theIPMN-risk miRNAs, where x_(i) represents miRNA i expression level, w_(i)is the corresponding weight (loading coefficient) with DV?=1, and thew_(i) values maximize the variance of Σw_(i)x_(i). This approach hasbeen used to derive a malignancy-risk gene signature previously (70,71).Receiver operating characteristic (ROC) curves were generated to measurethe predictive power of the IPMN-risk signature in discriminatingbetween groups.

Pathway Enrichment Analysis: To explore the potential roles ofidentified circulating miRNAs in pancreatic carcinogenesis, we appliedpathway-based bioinformatics exploratory analysis. Using Tarbase 6.0, weobtained a list of genes experimentally-validated to target theidentified miRNAs. The target genes were then analyzed to identifyenriched KEGG pathways (see worldwideweb.genome.jp/kegg/) that arepredicted to be regulated by these circulating miRNAs.

Identification of a plasma miRNA signature to differentiate betweenmalignant and benign IPMNs: We also used LIMMA (69) and the PCA approach(70,71) to identify a miRNA signature that distinguishes betweenmalignant (pathologically-confirmed as high-grade or invasive) andbenign IPMNs (pathologically-confirmed as low- or moderate-grade). Anunadjusted alpha of 0.05 was used as a threshold for inclusion in thesignature. To evaluate possible associations between selected predictorsof malignant potential (i.e., main-duct involvement, lesion size, serumCA-19-9 level) (8) and IPMN-risk status (malignant vs. benign), we usedthe Wilcoxon Rank Sum test and the Chi-squared test for continuous andcategorical variables, respectively. The exact method with Monte Carloestimation was used for both variable types. Multivariable logisticregression analysis was then conducted to assess whether the identifiedmiRNA signature was associated with malignant IPMN status independent ofselected variables. To assess the accuracy and clinical utility ofcandidate miRNAs in differentiating between malignant and benign IPMNs,ROC curves were constructed using the normalized miRNA count values andPC1, with pathological diagnosis as the gold standard.

Exploring paired tissue and circulating miRNA expression: Since apositive correlation between tissue and plasma miRNAs may be indicativeof a functional relationship, we identified 12 IPMN cases (4 low-grade,8 high-grade) with plasma successfully analyzed in the current study whohad matching tumor tissue that underwent genome-wide miRNA profiling aspart of a previous investigation using qRT-PCR technology (54). We usedSpearman correlations to evaluate the relationship between meanabundance of each miRNA in pre-operative plasma compared to pairedtissue.

All statistical analyses were performed using SAS version 9.4 and Rversion 3.11. To visualize miRNA expression patterns, we generatedheatmaps and performed unsupervised, hierarchical clustering.

Example 2—Plasma MicroRNAs as Novel Biomarkers of Disease for Patientswith Intraductal Papillary Mucinous Neoplasms of the Pancreas

Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause ofcancer deaths in the United States, with a five-year survival rate ofonly 6% (51). Approximately 85% of cases present with metastasis, whichcan be partly explained by a lack of sensitive and specific methods todetect disease at an early, operable stage (51). Based on a two-decadewindow of opportunity for early detection efforts in PDAC (6), anemerging paradigm is that the detection and treatment of noninvasiveprecursor lesions may offer the greatest hope in reducing PDAC morbidityand mortality. Three noninvasive PDAC precursor lesions (‘precancers’)that progress from low- and moderate-grade dysplasia to high-gradedysplasia and invasive carcinoma have been identified: pancreaticintraepithelial neoplasia (PanIN), mucinous cystic neoplasms (MCNs), andintraductal papillary mucinous neoplasms (IPMNs) (52,2). PanINs aremicroscopic lesions, while MCNs and IPMNs are macroscopic cystsaccounting for over half of the 150,000 asymptomatic pancreatic cystsdetected incidentally in the general population each year by imaging(4). IPMNs and PanINs have also been detected in those at high geneticrisk for PDAC (53). Once detected, invasive procedures such asendoscopic ultrasounds are often performed to assess the degree ofdysplasia, but imaging features and biomarkers obtained from suchprocedures do not reliably predict disease severity pre-operatively (2).Less invasive approaches are needed to aid in IPMN diagnosis andtreatment and to prevent progression to malignancy.

miRNAs are non-coding RNAs that regulate nearly one-third of allprotein-coding genes and promote carcinogenesis by regulating tumorsuppressors and oncogenes or serving these functions themselves (15).miRNAs are excellent candidate biomarkers of early disease because oftheir tissue-specific expression patterns (15), their remarkablestability in tissue (16) and biofluids (46) due to their small size andprotection from endogenous RNase activity, and their ability to regulatehundreds of genes and biological pathways (15). Recent studies by ourgroup (54) and others (5,29,44) have evaluated genome-wide miRNAexpression in IPMN tissue, and provide data to suggest that key miRNAsmay reliably differentiate low-risk/benign IPMNs (i.e., low- andmoderate-grade) that can be monitored from high-risk/malignant IPMNs(i.e., high-grade and invasive) that should be surgically resected.These tissue-based findings combined with discoveries that miRNAs can bereadily and reliably detected in systemic circulation (46,17) raise thepossibility that a minimally-invasive, cost-effective test thatcapitalizes on blood levels of miRNAs may be able to differentiatebetween individuals with IPMNs and non-diseased controls and betweenmalignant and benign IPMNs.

Although several studies (55-57) have evaluated miRNA expression inplasma, serum, or whole blood of PDAC patients and healthy controls, theimplications for early detection were limited because most cases hadlocally advanced or metastatic disease. Of two recent studies (48,58)that focused on evaluating blood-based genome-wide miRNA expression inearly-stage PDAC patients versus controls, one (48) includedpre-operative serum from patients with IPMNs (N=20; 4 low-grade; 16moderate-/high-grade). Li et al. (48) measured 735 miRNAs by qRT-PCRusing Taqman MicroRNA Arrays, and found that serum levels of miR-1290were significantly higher among the 20 patients with IPMNs compared tohealthy controls (area underneath the curve (AUC)=0.76 (95% confidenceinterval (CI): 0.61-0.91)). Although promising, these findings warrantreplication in a larger, independent population. Additionally, sincemost miRNAs are present in low quantities in blood, PCR-based methodsare limited in their ability to accurately detect and quantify miRNAlevels and can require pre-amplification which may compromisemeasurement reliability (57).

The primary objective of the current study was to determine thefeasibility of measuring the abundance of 800 miRNAs in archived plasmaobtained pre-operatively from individuals newly-diagnosed with IPMNs anddisease-free controls using a novel digital amplification-freequantification and comparison method called NCOUNTER™ technology(Nanostring, Inc., Seattle, Wash.) (59). Through an exploratoryanalysis, we then sought to discover a panel of circulating miRNAs thatmay a) differentiate between patients with IPMNs and non-diseasedcontrols, b) distinguish malignant from benign IPMNs, and/or c) reflectthe paired tumor miRNA expression profile. To our knowledge, this is thefirst study to conduct genome-wide profiling of circulating miRNAsexclusively among patients with cancer precursors using novel digitaltechnology.

Development of a minimally invasive blood-based assay for the earlydetection and management of pancreatic cancer precursors such asintraductal papillary mucinous neoplasms (IPMNs) is urgently needed toreduce the risks associated with invasive diagnostic approaches and tohelp prevent progression to incurable pancreatic malignancy. Based onthe hypothesis that differentially expressed microRNAs (miRNA) may beshed from IPMN tissues and detected in circulation, the inventorsconducted the first study that aimed to identify plasma miRNAs thatcould distinguish patients with IPMNs from healthy controls. Using novelNCOUNTER™ technology to evaluate 800 miRNAs in archived plasma, theinventors show that a signature containing 30 miRNAs distinguished 42IPMN cases from 24 healthy controls (area underneath the curve(AUC)=74.4 (95% CI:62.3-86.5, p=0.002)). The signature contained novelmiRNAs and miRNAs previously implicated in pancreatic carcinogenesisthat had 2 to 4-fold higher expression in cases than controls. Theinventors also generated a 5-miRNA signature that discriminated between21 malignant and 21 benign IPMNs (AUC=73.2 (95% CI: 57.6-73.2,p=0.005)), and provide data to suggest that paired plasma and tissuesamples from patients with IPMNs can have distinct miRNA expressionprofiles. These findings demonstrate the feasibility of using newcost-effective digital technology to reliably develop aminimally-invasive assay to measure plasma miRNA expression and aid inIPMN management.

A. Study Population

Pre-operative plasma samples were evaluated for 44 IPMN cases (5low-grade, 18 moderate-grade, 13 high-grade, and 8 invasive) and 25non-diseased controls that were frequency-matched to cases on age-groupand gender. Three samples (2 from cases and 1 from a control) wereexcluded prior to normalization and statistical analysis due to presumedcellular contamination characterized by ribosomal RNA bands or high mRNAcounts, leaving a total of 66 subjects (42 pathologically-confirmed IPMNcases, 24 controls) for analysis. Characteristics of the analyzed casesand controls are shown in Table 7. Cases and controls were well-matchedon age (mean age: 69.0 vs 69.1). Most subjects were white, non-Hispanic,and the majority were current or previous smokers without a familyhistory of PDAC. The distribution of low-, moderate-, high-grade, andinvasive IPMN cases represented in this study was 9.5%, 40.5%, 31%, and19%, respectively.

TABLE 7 Characteristics of the Study Population (N = 66). IPMN Healthycases controls Variable (n = 42) (n = 24) Age at diagnosis/interview,mean 69.0 (10.7) 69.1 (9.6)  (SD)(yrs) Gender, male:female, n (%) 19:23(45:55) 12:12 (50:50) Race, n (%) White, Non-Hispanic 37 (88)  24 (100)Other 5 (12) 0 (0) Family history of pancreatic cancer, n (%) Yes 4 (17)1 (4) No 15 (83) 23 (96) Ever Smoker, n (%) Yes 21 (50) 11 (46) No 21(50)  3 (13) Unknown 0 (0) 10 (42) IPMN Grade, n (%) Low 4 (9.5) —Moderate 17 (40.5) — High 13 (31) — Invasive 8 (19) — Data representcounts (percentages) unless otherwise indicated. Counts may not add upto the total due to missing values, and percentages may not equal 100due to rounding.

B. Exploratory Analysis of Circulating miRNAs in IPMNS VersusNon-Diseased Controls

A total of 558 of the 800 miRNAs evaluated (69.8%) had more than 80% ofsignals below background and were excluded, leaving 242 miRNAs fornormalization and statistical analysis. This proportion of detectablecirculating miRNAs is comparable or better than that of other studies(58,72-74) and demonstrates the NCOUNTER platform's ability to detect asizeable number of miRNAs using archived plasma samples. No differencein the frequency or the amount of hemolysis as measuredspectrophotometrically or by hemolysis-related miRNA analysis wasobserved in the case versus control samples.

After technical normalization with spike-in oligos and biologicalnormalization with the most invariant miRNAs in the dataset (miR-378,miR-579, miR-30e-5p, and miR-570-3p), 30 miRNAs differentiated betweenIPMN cases and controls using an FDR<0.15. The 30 miRNAs include:let-7a-5p, let-7d-5p, let-7f-5p, let-7g-5p, let-7i-5p, miR-107,miR-1260b, miR-126-3p, miR-142-3p, miR-145-5p, miR-146a-5p, miR-148a-3p,miR-15b-5p, miR-181a-5p, miR-191-5p, miR-199a-3p, miR-199b-3p,miR-20a-5p, miR-20b-5p, miR-22-3p, miR-23a-3p, miR-24-3p, miR-26a-5p,miR-27a-3p, miR-29c-3p, miR-335-5p, miR-337-5p, miR-340-5p, miR-423-5p,miR-4454, miR-593-3p, and miR-98. The candidate miRNAs had 2.09-4.32fold higher expression as defined by mean normalized counts in theplasma of cases as opposed to controls (Table 8). The circulating miRNAthat was most significantly associated with IPMN case status wasmiR-145-5p (t-test P=8.6×10⁻⁵), with expression levels 3.78 fold higherin cases than controls and an AUC value of 0.79 (95% CI: 69.3-90.3) inclassifying between IPMNs and healthy controls (Table 8; FIGS. 12A and12B).

TABLE 8 The top 30 miRNAs deregulated in plasma of IPMN cases versusnon-diseased controls Mean Mean Normalized Normalized False Counts CasesCounts Controls Fold- Discovery miRNA ID (n = 42) (n = 24) Change P RateAUC (95% CI) hsa-miR-145-5p 3.26 1.34 3.78 8.61E−05 0.0208 79.3 (68.3,90.3) hsa-miR-4454 10.58 9.46 2.18 0.0018 0.1043 72.4 (59.6, 85.2)hsa-let-7f-5p 8.27 6.38 3.69 0.0028 0.1043 73.8 (62.0, 85.6)hsa-miR-146a-5p 8.55 6.55 4.00 0.0032 0.1043 72.4 (60.2, 84.6)hsa-let-7d-5p 7.33 5.42 3.75 0.0043 0.1043 69.1 (55.7, 82.4)hsa-let-7a-5p 11.43 9.83 3.05 0.0044 0.1043 68.6 (55.2, 81.9)hsa-miR-142-3p 12.71 11.29 2.68 0.0060 0.1043 67.2 (53.3, 81.0)hsa-miR-423-5p 8.62 7.04 2.99 0.0061 0.1043 69.4 (56.2, 82.7)hsa-miR-22-3p 10.06 8.93 2.18 0.0072 0.1043 68.8 (55.8, 81.7)hsa-miR-107 7.64 5.84 3.48 0.0073 0.1043 72.3 (59.3, 85.4)hsa-miR-29c-3p 6.97 5.11 3.63 0.0076 0.1043 67.4 (53.6, 81.1)hsa-miR-148a-3p 8.23 6.50 3.31 0.0078 0.1043 70.8 (57.8, 83.9)hsa-miR-340-5p 5.28 3.18 4.32 0.0079 0.1043 70.8 (57.5, 84.2)hsa-miR-181a-5p 5.36 3.34 4.06 0.0079 0.1043 69.6 (56.6, 82.7)hsa-miR-335-5p 3.44 1.92 2.87 0.0083 0.1043 69.4 (56.3, 82.6)hsa-let-7i-5p 8.79 7.31 2.80 0.0092 0.1043 71.0 (58.3, 83.7)hsa-miR-337-5p 3.19 1.71 2.79 0.0092 0.1043 71.4 (58.2, 84.7)hsa-miR-1260b 3.28 1.63 3.15 0.0093 0.1043 67.9 (54.6, 81.1)hsa-miR-593-3p 2.46 1.40 2.09 0.0097 0.1043 68.7 (55.2, 82.1)hsa-miR-27a-3p 4.29 2.61 3.20 0.0097 0.1043 68.8 (55.3, 82.2)hsa-let-7g-5p 11.95 10.70 2.38 0.0099 0.1043 68.5 (55.4, 81.5)hsa-miR-191-5p 10.56 9.29 2.40 0.0100 0.1043 68.2 (54.9, 81.4)hsa-miR-24-3p 8.15 6.21 3.83 0.0100 0.1043 69.4 (56.3, 82.4)hsa-miR-20a-5p + 10.36 9.15 2.30 0.0103 0.1043 68.1 (54.9, 81.2) hsa-miR-20b-5p hsa-miR-26a-5p 10.23 8.91 2.50 0.0114 0.1100 72.4 (60.2,84.6) hsa-miR-23a-3p 11.16 10.05 2.16 0.0130 0.1206 66.7 (53.2, 80.2)hsa-miR-199a-3p + 10.53 8.95 2.99 0.0150 0.1344 69.5 (56.5, 82.6)hsa-miR-199b-3p hsa-miR-126-3p 13.23 11.90 2.51 0.0168 0.1406 65.8(52.0, 79.5) hsa-miR-98 4.12 2.51 3.05 0.0174 0.1406 67.4 (54.0, 80.8)hsa-miR-15b-5p 11.24 9.83 2.65 0.0174 0.1406 65.8 (52.3, 79.3)Abbreviations: AUC = Area underneath the curve; CI = confidence intervalComparisons conducted with t-tests

The 30 miRNA IPMN-risk signature was analyzed using PCA to evaluate thepercent of variability and loading coefficients by PC1 (i.e. theIPMN-risk score). PC1 explained 64% of the variability, suggesting itrepresents the 30 miRNA IPMN-risk signature well (FIG. 10A). The overallexpression of PC1 was higher in cases as compared to controls (p=0.002,FIG. 10B). Moreover, the continuous PC1 score for the 30-miRNA signatureshowed a significant association with IPMN status (odds ratio (OR) 95%CI:=1.23 (1.07-1.41), p=0.003) and had an AUC value of 74.4 (95% CI:62.3-86.5) in discriminating between IPMN patients and healthy controls(FIG. 10C). A heatmap of gene expression for the 30 miRNA signature inour cohort is displayed in FIGS. 11A-11D. Pathway enrichment analysisrevealed numerous pathways that are predicted to be regulated by the 30miRNA IPMN-risk signature (FIGS. 13A-13D), with ‘Pathways in Cancer’ and‘p53 signaling’ comprising the most significantly predicted pathwayswith p=1.3×10⁻²⁶ and p=1.2×10⁻²⁴, respectively.

C. Exploratory Analysis of Circulating miRNAs in Malignant Versus BenignIPMNs

For exploratory purposes, we evaluated the ability of the 30-miRNAsignature represented by PC1 to discriminate between the 21 malignantand 21 benign IPMN cases. We observed that the signature did notaccurately differentiate between malignant and benign IPMNs (AUC=60.8(95% CI: 42.5-79.1)). However, after performing LIMMA and PCA analysisexclusively on the 42 IPMN cases, circulating levels of five miRNAs(miR-200a-3p, miR-1185-5p, miR-33a-5p, miR-574-3p, and miR-663b)discriminated between the malignant and benign IPMN groups (p<0.05)(Table 9). The 5 miRNA IPMN-risk signature was analyzed using PCA toevaluate the percent of variability and loading coefficients by PC1. PC1explained 50% of the variability (FIG. 14A). The overall expression ofPC1 was higher in benign compared to malignant IPMNs (p=0.005, FIG.14B). Moreover, the continuous PC1 score for the 5-miRNA signatureshowed a significant association with malignant status (OR (95% CI):=0.36 (0.16, 0.83), p=0.017) and had an AUC value of 73.2 (95% CI:57.6-88.9) in discriminating between groups (FIG. 14C). Multivariablelogistic regression revealed that the PC1 score for the 5-miRNAsignature was not independently associated with malignant status afteradjustment for main duct involvement (p=0.008), a predictor of malignantpotential that can be detected by imaging.

TABLE 9 MiRNA expression in Malignant (N = 21) versus Benign (N = 21)IPMN cases Mean Mean False expression expression Discovery miRNA IDmalignant cases benign cases Fold-Change P Rate AUC (95% CI)hsa-miR-200a-3p 1.615771833 2.966035816 2.549587734 0.030625 0.94242239863.49 (45.74, 81.24) hsa-miR-1185-5p 3.30508802 4.663054049 2.5632354920.0362 0.942422398 66.67 (49.71, 83.62) hsa-miR-33a-5p 4.1971487685.760001269 2.954374061 0.036233 0.942422398 70.29 (53.84, 86.75)hsa-miR-574-3p 2.684391746 4.089466711 2.648315428 0.042473 0.94242239867.57 (50.33, 84.82) hsa-miR-663b 1.345295736 2.559839402 2.3206736680.045826 0.942422398 45.58 (27.33, 63.83) hsa-miR-99b-5p 3.2166127674.606655552 2.620864532 0.050763 0.942422398 63.04 (45.02, 81.06)hsa-miR-626 2.242417221 3.5535875 2.481427458 0.051473 0.942422398 64.4(46.86, 81.93) hsa-miR-431-5p 2.277640545 3.44308567 2.2430241070.052351 0.942422398 65.76 (47.89, 83.63) hsa-miR-548am-3p 2.8113720491.847526035 1.950502724 0.063424 0.942422398 74.15 (58.88, 89.42)hsa-miR-766-3p 2.246317884 3.397633119 2.221162949 0.066287 0.94242239858.5 (40.06, 76.95) hsa-miR-325 1.761160582 3.021185483 2.3949987470.068005 0.942422398 62.13 (44.4, 79.86) hsa-miR-340-5p 4.4507713516.128155372 3.198474588 0.071935 0.942422398 62.59 (44.37, 80.8)hsa-miR-423-3p 3.497204436 4.824352297 2.509061549 0.072879 0.94242239863.04 (44.7, 81.38) hsa-miR-125a-5p 4.153821563 5.835689051 3.2084299560.073317 0.942422398 61.22 (42.21, 80.24) hsa-miR-891b 1.404125782.38490016 1.973524433 0.075251 0.942422398 57.14 (38.57, 75.72)hsa-miR-4443 5.471587884 7.553436401 4.233493039 0.075369 0.94242239867.12 (49.84, 84.4) hsa-miR-152 2.668170778 3.773973482 2.1521859070.088186 0.942422398 59.86 (41.51, 78.22) hsa-miR-337-3p 3.2896407534.542330799 2.382853153 0.103 0.942422398 59.18 (40.73, 77.64)hsa-miR-432-5p 2.329661787 3.345909559 2.022651507 0.10316 0.94242239859.41 (40.65, 78.17) hsa-miR-518b 7.553215211 8.51841713 1.952336750.104286 0.942422398 72.79 (57.22, 88.36) hsa-miR-151a-3p 6.5252861117.785322099 2.395017152 0.104296 0.942422398 63.95 (46.45, 81.44)hsa-miR-301a-3p 4.749355407 6.040712701 2.447582168 0.104688 0.94242239862.81 (45.38, 80.24) hsa-miR-324-5p 3.622046418 4.984271817 2.5708142950.110909 0.942422398 60.32 (41.61, 79.02) hsa-miR-363-3p 3.6587568445.233824249 2.97949413 0.111376 0.942422398 60.54 (42.13, 78.96)hsa-miR-28-5p 5.277202334 6.311696999 2.048396026 0.116503 0.94242239862.81 (45.44, 80.18) hsa-miR-590-5p 7.012386539 7.758008003 1.6766963780.12366 0.942422398 62.81 (45.54, 80.08) hsa-miR-23b-3p 4.0327103655.324122578 2.447675344 0.12729 0.942422398 59.64 (41.26, 78.02)hsa-miR-656 3.738385956 4.795142843 2.080249954 0.13051 0.94242239862.81 (45.5, 80.12) hsa-miR-27b-3p 6.358658637 7.750298731 2.6237678820.132811 0.942422398 64.63 (47.4, 81.85) hsa-miR-450a-5p 2.8298039813.830108875 2.000422718 0.142842 0.942422398 59.18 (40.98, 77.39)hsa-miR-323a-3p 3.001192263 4.227602918 2.339841257 0.143145 0.94242239861.68 (43.8, 79.56) hsa-miR-374b-5p 5.909592739 7.214609192 2.4708654520.154409 0.942422398 65.31 (48.01, 82.6) hsa-miR-769-5p 5.9020901626.717782712 1.760142886 0.154848 0.942422398 65.76 (48.21, 83.31)hsa-miR-598 8.033655579 8.686225219 1.571965593 0.156413 0.94242239863.04 (44.77, 81.31) hsa-let-7e-5p 2.649924375 3.686594428 2.0514870570.156889 0.942422398 56.92 (38.69, 75.14) hsa-miR-1246 7.6988089176.065808623 3.101573457 0.166295 0.942422398 65.08 (47.96, 82.2)hsa-miR-1183 6.430538854 7.500899759 2.099958628 0.167408 0.94242239864.17 (46.73, 81.61) hsa-miR-503 2.542922227 3.5421607 1.9989445780.168895 0.942422398 55.56 (36.82, 74.3) hsa-miR-145-5p 2.8092300133.704919727 1.860499127 0.170114 0.942422398 57.37 (38.54, 76.2)hsa-miR-520f 14.74582444 14.21943187 1.440323193 0.171418 0.94242239863.95 (46.92, 80.98) hsa-miR-199a-3p + 10.07926225 10.984802761.873246171 0.172369 0.942422398 61.9 (44.3, 79.51) hsa-miR-199b-3phsa-miR-409-3p 3.530767091 4.592448331 2.087362605 0.177634 0.94242239856.69 (38.28, 75.1) hsa-miR-107 7.149547583 8.138766822 1.9851103930.178718 0.942422398 66.21 (49.19, 83.24) hsa-miR-181a-5p 4.7462501695.97538226 2.344259194 0.179448 0.942422398 61 (42.21, 79.79)hsa-miR-18a-5p 6.321189577 7.167105787 1.79740586 0.180714 0.94242239862.81 (45.49, 80.13) hsa-miR-219-5p 3.846317526 4.885776949 2.055457330.184777 0.942422398 64.17 (46.72, 81.62) hsa-miR-761 5.4441896686.49773429 2.07562328 0.186382 0.942422398 64.85 (47.4, 82.3)hsa-miR-136-5p 2.269815944 3.233955453 1.950899567 0.191013 0.94242239852.61 (33.89, 71.33) hsa-miR-361-5p 5.297989314 6.547116924 2.376976450.197897 0.942422398 58.96 (40.75, 77.16) hsa-miR-378a-3p + 2.8870986672.164701522 1.649921225 0.199155 0.942422398 67.12 (50.33, 83.91)hsa-miR-378i hsa-miR-199a-5p 7.446858231 8.482077163 2.0494246270.206348 0.942422398 64.63 (47.49, 81.76) hsa-miR-376a-3p 5.2543493496.435834206 2.268100956 0.208832 0.942422398 60.09 (42.32, 77.86)hsa-miR-335-5p 2.963842605 3.910833708 1.927847727 0.209464 0.94242239856.92 (38.63, 75.2) hsa-miR-641 2.383608366 1.812532861 1.485630670.213825 0.942422398 70.75 (54.31, 87.19) hsa-let-7d-5p 6.8752784297.782075876 1.874878944 0.216245 0.942422398 64.4 (46.82, 81.98)hsa-miR-515-5p 1.771671055 2.492186146 1.64777024 0.219054 0.94242239846.49 (27.85, 65.12) hsa-miR-24-3p 7.644710385 8.651529824 2.0094761280.221976 0.942422398 63.27 (45.91, 80.62) hsa-miR-548a-3p 2.5977336333.481908316 1.845708452 0.228709 0.954268456 58.28 (40.07, 76.48)hsa-miR-720 6.097764926 7.022095499 1.897803436 0.233878 0.95929431 61.9(44.47, 79.34) hsa-miR-125b-5p 6.211103968 5.302946467 1.8766472580.245976 0.975564671 58.96 (40.7, 77.22) hsa-miR-10a-5p 2.2996996171.738028042 1.475978366 0.24834 0.975564671 64.17 (46.8, 81.54)hsa-miR-4454 10.37523516 10.78558888 1.32901162 0.250944 0.97556467162.59 (45, 80.17) hsa-miR-376c 3.692307708 4.81424283 2.1763870080.257087 0.975564671 54.42 (36.01, 72.83) hsa-miR-370 3.1223152023.998907771 1.836033738 0.258001 0.975564671 60.77 (43.12, 78.42)hsa-miR-28-3p 3.152179301 3.903257667 1.683050385 0.264833 0.98599456355.78 (37.38, 74.18) hsa-miR-1323 2.482505819 1.928638163 1.4680159630.271323 0.994850457 69.39 (52.24, 86.54) hsa-miR-548ad 3.3618398414.115826376 1.686446481 0.292215 0.996834076 59.41 (41.43, 77.39)hsa-miR-448 4.466225515 5.148164698 1.604294702 0.293465 0.99683407658.5 (40.74, 76.26) hsa-miR-548d-3p 3.78738083 4.548729888 1.6950749410.305973 0.996834076 56.69 (38.37, 75.01) hsa-miR-593-3p 2.7600595432.170380491 1.504911922 0.307035 0.996834076 68.48 (51.65, 85.31)hsa-miR-19a-3p 6.973932847 7.83962719 1.822216455 0.315139 0.99683407654.88 (36.89, 72.87) hsa-miR-1281 2.127607896 1.692206645 1.3522868870.321062 0.996834076 69.84 (52.73, 86.95) hsa-miR-1202 2.42861241.984872148 1.360125948 0.323373 0.996834076 67.12 (49.85, 84.39)hsa-miR-574-5p 3.672028665 4.30337344 1.549008193 0.323898 0.99683407656.92 (38.79, 75.04) hsa-miR-548p 2.512748513 3.226312145 1.6398497470.325915 0.996834076 56.01 (37.87, 74.14) hsa-miR-513b 8.3531845117.279216093 2.105216225 0.330261 0.996834076 59.18 (41.49, 76.88)hsa-miR-1976 13.80073147 13.36453869 1.353029018 0.336869 0.99683407661.68 (43.88, 79.48) hsa-miR-151a-5p 3.26409737 3.966714925 1.627454890.336948 0.996834076 53.97 (35.41, 72.53) hsa-miR-338-3p 4.7278869565.593815637 1.822512464 0.337374 0.996834076 58.05 (40.04, 76.06)hsa-miR-486-3p 4.174794941 3.479885515 1.618782802 0.342787 0.99683407661.45 (44.09, 78.81) hsa-miR-4458 2.721133954 2.205775111 1.4293496190.347082 0.996834076 65.76 (48.39, 83.13) hsa-miR-663a 2.4694319273.12894064 1.579544642 0.34948 0.996834076 45.12 (26.27, 63.98)hsa-miR-487b 2.18249922 2.751554711 1.483551995 0.359648 0.99683407649.21 (30.74, 67.67) hsa-miR-331-3p 3.204689676 3.786014944 1.4962230560.364513 0.996834076 56.24 (37.8, 74.67) hsa-miR-548k 1.8884216652.455054405 1.481062723 0.368103 0.996834076 48.53 (30.16, 66.89)hsa-let-7a-5p 11.21513275 11.65269129 1.354310496 0.370617 0.99683407661 (42.84, 79.16) hsa-miR-660-5p 4.921246232 5.582434396 1.5813844730.374541 0.996834076 56.24 (37.9, 74.57) hsa-miR-27a-3p 3.9308108424.644520486 1.64001572 0.377622 0.996834076 55.1 (36.83, 73.38)hsa-miR-34c-5p 4.103426644 4.877888542 1.710551924 0.378155 0.99683407656.92 (38.88, 74.95) hsa-miR-98 3.732228753 4.500835617 1.7036238870.380142 0.996834076 51.93 (33.1, 70.76) hsa-miR-1208 2.5327971412.079364521 1.369294362 0.383502 0.996834076 65.08 (47.75, 82.4)hsa-miR-382-5p 2.792415652 3.374383889 1.49689003 0.389714 0.99683407654.2 (35.91, 72.48) hsa-miR-337-5p 2.866781287 3.510291351 1.5621251760.390578 0.996834076 50.11 (31.29, 68.94) hsa-miR-494 1.9229239872.375462179 1.368445703 0.396433 0.996834076 46.49 (28.33, 64.64)hsa-miR-630 7.035153992 6.602852107 1.349384865 0.400513 0.99683407658.73 (41.05, 76.41) hsa-miR-221-3p 7.789072228 8.541239726 1.6843214470.407257 0.996834076 63.27 (45.54, 80.99) hsa-miR-30d-5p 5.9631055396.701338067 1.668130929 0.408002 0.996834076 47.39 (29.04, 65.74)hsa-miR-484 4.350882237 5.0082803 1.577235472 0.410254 0.996834076 55.33(37.2, 73.45) hsa-miR-23c 5.051370615 5.808674143 1.690328359 0.419220.996834076 62.13 (44.33, 79.93) hsa-miR-367-3p 2.647935062 2.1944531531.369341143 0.427611 0.996834076 64.85 (47.58, 82.12) hsa-miR-44554.094985919 4.905756248 1.754147822 0.431881 0.996834076 56.24 (38.03,74.44) hsa-miR-450b-5p 2.247451804 2.763970227 1.430498934 0.4394330.996834076 47.62 (29.29, 65.95) hsa-miR-32-5p 5.919864275 6.5413330421.538440628 0.443265 0.996834076 59.18 (41.5, 76.87) hsa-miR-3184-5p1.519863447 1.920409697 1.320007613 0.445155 0.996834076 50.57 (32.11,69.02) hsa-miR-499a-3p 3.603921629 4.093124046 1.403668654 0.4520140.996834076 53.29 (35.08, 71.5) hsa-miR-570-3p 6.986151053 7.2080223231.166245303 0.452242 0.996834076 61.68 (44.09, 79.27) hsa-miR-140-5p4.923283985 5.543787944 1.537412133 0.46422 0.996834076 56.69 (37.93,75.45) hsa-miR-92a-3p 9.683209011 9.264193096 1.337015245 0.4662980.996834076 53.29 (35.37, 71.21) hsa-miR-29a-3p 3.932950816 4.4739463481.454976177 0.480011 0.996834076 55.33 (36.94, 73.71) hsa-miR-5681.768620581 2.148120108 1.300890496 0.484649 0.996834076 50.79 (32.29,69.3) hsa-miR-1277-3p 5.780183603 6.214332418 1.351113446 0.4865760.996834076 58.5 (40.61, 76.4) hsa-miR-142-3p 12.55342461 12.876877361.251321714 0.490237 0.996834076 59.18 (41.24, 77.13) hsa-miR-21-5p12.12285373 11.8071901 1.244584021 0.493516 0.996834076 50.79 (32.57,69.02) hsa-miR-4425 2.656438178 2.323466084 1.259605615 0.5162380.996834076 62.59 (44.76, 80.41) hsa-miR-425-5p 6.910915141 7.4406091461.443622971 0.517845 0.996834076 58.28 (40.54, 76.02) hsa-let-7f-5p8.046608441 8.491764362 1.361461249 0.519651 0.996834076 59.86 (42.05,77.68) hsa-miR-451a 16.75525225 17.19360397 1.35505529 0.5216310.996834076 55.56 (37.39, 73.72) hsa-miR-1244 4.465937341 4.0216894061.36060466 0.526662 0.996834076 43.08 (25.17, 61) hsa-miR-342-3p7.850981879 8.329399207 1.393214437 0.537409 0.996834076 50.79 (32.66,68.93) hsa-miR-320e 9.071504899 8.851915053 1.164402503 0.5418210.996834076 60.77 (42.49, 79.05) hsa-miR-155-5p 3.050058047 2.5728066221.392088976 0.544862 0.996834076 66.67 (48.67, 84.67) hsa-miR-20531.743239398 1.997695342 1.192885808 0.553128 0.996834076 50.34 (31.81,68.87) hsa-miR-146a-5p 8.344249959 8.758352711 1.332469724 0.5552140.996834076 60.09 (42.02, 78.16) hsa-miR-548x-3p 3.339910951 2.9617460251.299687631 0.556118 0.996834076 61.68 (44.06, 79.29) hsa-miR-23a-3p11.02769168 11.29522058 1.203744242 0.568127 0.996834076 61 (43, 79)hsa-miR-659-3p 2.113285438 2.472081748 1.282355537 0.568162 0.99683407650.34 (31.93, 68.75) hsa-miR-26b-5p 10.46033422 10.1321358 1.2554446410.571187 0.996834076 49.43 (31.1, 67.76) hsa-miR-4286 2.2537260262.025370168 1.17149911 0.588749 0.996834076 59.41 (41.55, 77.27)hsa-miR-141-3p 2.714106218 3.09891731 1.305688808 0.592149 0.99683407654.2 (35.57, 72.82) hsa-miR-548g-3p 3.747155144 4.178211443 1.3482203420.592427 0.996834076 51.25 (32.75, 69.74) hsa-miR-127-3p 2.2768154662.580870687 1.234609862 0.595809 0.996834076 54.2 (35.23, 73.16)hsa-miR-148a-3p 8.051708898 8.409785103 1.281715625 0.604962 0.99683407661.22 (43.39, 79.06) hsa-miR-891a 1.689229414 1.953522835 1.2010476760.60739 0.996834076 57.37 (38.77, 75.97) hsa-miR-223-3p 13.4038274513.65790857 1.192575928 0.629325 0.996834076 57.82 (39.79, 75.85)hsa-miR-612 3.937772313 3.6315993 1.236423528 0.639314 0.996834076 58.73(40.98, 76.48) hsa-miR-548ah-5p 3.814550838 3.343399476 1.3862153140.639738 0.996834076 65.76 (48.4, 83.12) hsa-miR-4461 3.0228147372.750007917 1.208156058 0.641477 0.996834076 57.6 (39.57, 75.63)hsa-miR-548ae 3.436200466 2.964901886 1.386356777 0.646207 0.99683407667.8 (50.9, 84.7) hsa-miR-106a-5p + 11.21571472 10.98352515 1.1746163040.648139 0.996834076 49.89 (31.79, 67.98) hsa-miR-17-5p hsa-miR-149-5p2.995367011 2.750037131 1.185363779 0.649278 0.996834076 45.58 (27.54,63.61) hsa-miR-188-5p 6.894520506 6.664756851 1.172642829 0.6500290.996834076 55.56 (37.69, 73.42) hsa-miR-126-3p 13.12840359 13.336402621.155085008 0.654684 0.996834076 58.73 (40.47, 76.99) hsa-miR-30a-5p4.017230996 4.339258427 1.250086071 0.655908 0.996834076 51.25 (32.71,69.79) hsa-miR-15a-5p 10.67056453 10.43444612 1.177819452 0.662220.996834076 51.25 (33.15, 69.35) hsa-miR-219-1-3p 2.0548307151.801884766 1.191637928 0.66891 0.996834076 61.22 (42.91, 79.54)hsa-miR-423-5p 8.746556611 8.495619566 1.189979768 0.676222 0.99683407656.01 (37.94, 74.07) hsa-miR-410 2.742735273 2.477024067 1.2022285660.680498 0.996834076 60.54 (42.88, 78.21) hsa-miR-2682-5p 2.5858579642.834092615 1.187752835 0.684692 0.996834076 50.34 (32.01, 68.67)hsa-miR-548n 3.541473085 3.094501895 1.363175385 0.686065 0.99683407668.48 (51.82, 85.14) hsa-miR-122-5p 4.418589571 4.743225586 1.2523484380.696571 0.996834076 50.57 (32.45, 68.68) hsa-miR-566 2.2914895892.050604201 1.181717665 0.700093 0.996834076 58.5 (40.26, 76.75)hsa-miR-516a-5p 4.05254376 4.37317091 1.248873325 0.702564 0.99683407655.78 (37.75, 73.82) hsa-miR-544a 3.269776826 2.941893167 1.2551707680.703498 0.996834076 65.08 (47.43, 82.73) hsa-miR-888-5p 3.5679825613.91128205 1.268654732 0.706756 0.996834076 49.89 (31.62, 68.15)hsa-miR-222-3p 8.298565154 8.433322835 1.097908391 0.715667 0.99683407653.29 (35.23, 71.35) hsa-miR-19b-3p 10.4584327 10.25152898 1.1542083870.720014 0.996834076 51.25 (33.17, 69.32) hsa-miR-384 4.0121413224.310780532 1.229983711 0.722511 0.996834076 55.1 (37.09, 73.11)hsa-miR-654-3p 2.577708801 2.830902754 1.191842792 0.726261 0.99683407651.02 (32.6, 69.44) hsa-miR-130a-3p 9.655265129 9.901247801 1.1859002560.727607 0.996834076 61.68 (43.68, 79.68) hsa-miR-133b 1.8082215351.634282537 1.128134435 0.727716 0.996834076 61.68 (43.45, 79.91)hsa-miR-106b-5p 9.796119892 9.6015447 1.144387141 0.735906 0.99683407653.06 (34.94, 71.18) hsa-miR-212-3p 2.854409363 3.097930536 1.183878620.737562 0.996834076 52.15 (34.08, 70.23) hsa-miR-148b-3p 9.5020724589.68259505 1.133294327 0.740091 0.996834076 60.09 (42.23, 77.95)hsa-miR-495 8.414734728 8.605219093 1.141146776 0.742411 0.99683407659.86 (42.24, 77.49) hsa-miR-143-3p 3.309124258 3.012690203 1.2281051210.747466 0.996834076 63.27 (45.5, 81.04) hsa-miR-4421 3.0738071292.844055814 1.172632799 0.75307 0.996834076 63.04 (45.36, 80.72)hsa-miR-191-5p 10.47851698 10.64056505 1.118874381 0.75463 0.99683407658.28 (40.04, 76.51) hsa-miR-361-3p 2.802107592 2.633616964 1.1238820450.758668 0.996834076 56.24 (37.97, 74.5) hsa-miR-216b 2.4239640672.580196166 1.114372915 0.761938 0.996834076 48.75 (30.19, 67.32)hsa-miR-489 2.005520292 2.150126752 1.105429072 0.764528 0.99683407653.51 (35.09, 71.94) hsa-miR-186-5p 4.597934876 4.354784235 1.18357460.767095 0.996834076 57.6 (39.63, 75.56) hsa-miR-631 6.7693684976.876847691 1.077344159 0.774825 0.996834076 49.43 (31.29, 67.58)hsa-miR-302b-3p 5.704246106 5.999582003 1.227170662 0.777445 0.99683407653.06 (34.63, 71.49) hsa-miR-548aa 3.744032696 4.102374394 1.2819515150.778539 0.996834076 57.82 (39.73, 75.92) hsa-miR-652-3p 2.7726495992.594903064 1.131115721 0.782187 0.996834076 61 (43.09, 78.91)hsa-miR-1285-3p 3.344816956 3.062094539 1.216488276 0.782778 0.99683407663.04 (45.18, 80.9) hsa-miR-302d-3p 8.604243192 8.525896773 1.0558072070.793789 0.996834076 57.37 (39.41, 75.33) hsa-miR-30e-5p 8.9381013938.831890655 1.076397346 0.797944 0.996834076 54.88 (36.75, 73)hsa-miR-378e 9.971547907 9.90300378 1.048657913 0.798384 0.99683407650.79 (32.51, 69.07) hsa-miR-2117 3.101292385 3.267840089 1.1223694950.799186 0.996834076 48.3 (29.77, 66.83) hsa-miR-1827 4.5132243264.67710345 1.120295346 0.80128 0.996834076 51.47 (32.76, 70.19)hsa-miR-197-3p 5.828470549 6.060261839 1.174292078 0.807774 0.99683407650.34 (31.99, 68.69) hsa-miR-4531 2.942977952 2.743673747 1.1481444840.80901 0.996834076 61.9 (44.34, 79.47) hsa-miR-548q 2.8992530282.7198341 1.132427687 0.813173 0.996834076 61.68 (44.05, 79.3)hsa-miR-454-3p 3.220396019 3.031684916 1.139745019 0.814855 0.99683407654.88 (36.72, 73.03) hsa-miR-185-5p 9.588145329 9.685891741 1.0701005860.815781 0.996834076 52.61 (34.63, 70.58) hsa-miR-30b-5p 8.8107938028.643342532 1.123072661 0.820802 0.996834076 53.97 (35.82, 72.11)hsa-miR-514b-5p 4.065835965 4.227142113 1.118299136 0.828657 0.99683407650.34 (32.32, 68.36) hsa-miR-485-3p 2.582026554 2.72738064 1.106002070.829999 0.996834076 50.57 (32.48, 68.66) hsa-miR-580 2.2385662682.10249165 1.098911053 0.830568 0.996834076 56.92 (38.73, 75.1)hsa-miR-941 2.840288345 2.993389905 1.111957432 0.842178 0.99683407661.9 (43.7, 80.11) hsa-miR-627 3.449040503 3.29368285 1.1136976760.842972 0.996834076 58.73 (40.79, 76.67) hsa-miR-25-3p 11.1326195511.2161741 1.059625557 0.850995 0.996834076 52.15 (33.57, 70.74)hsa-miR-192-5p 6.17140045 6.087373875 1.059972308 0.85153 0.99683407654.42 (36.46, 72.39) hsa-miR-548ai 4.14284467 4.422964564 1.2142957930.855489 0.996834076 54.42 (36.34, 72.5) hsa-miR-374a-5p 10.4819306610.37253765 1.078774262 0.857539 0.996834076 55.1 (37.19, 73.01)hsa-miR-942 3.089149686 2.927286581 1.118730942 0.859653 0.99683407658.28 (40.45, 76.1) hsa-miR-1252 2.686655159 2.791346651 1.075264430.8605 0.996834076 44.9 (26.03, 63.76) hsa-miR-297 1.5455788641.621226244 1.053833817 0.861361 0.996834076 55.78 (37.24, 74.33)hsa-miR-487a 2.656305636 2.548103956 1.077883816 0.866809 0.99683407657.82 (39.9, 75.75) hsa-miR-26a-5p 10.17441552 10.27953529 1.0755836830.868268 0.996834076 57.14 (39.04, 75.25) hsa-miR-29c-3p 6.9088134957.034093467 1.090719379 0.870736 0.996834076 54.65 (36.64, 72.66)hsa-miR-519b-5p + 4.072545076 4.237777395 1.121346635 0.872750.996834076 47.85 (29.61, 66.08) hsa-miR-519c-5p hsa-miR-1537 2.502659742.58799252 1.060932433 0.87667 0.996834076 46.26 (27.68, 64.84)hsa-miR-579 6.510531519 6.463415115 1.033197749 0.878321 0.99683407653.06 (34.98, 71.15) hsa-miR-375 5.941039255 6.079026659 1.1003690020.878959 0.996834076 50.11 (31.86, 68.37) hsa-miR-93-5p 10.7390779710.80518263 1.04688623 0.882345 0.996834076 48.3 (30.08, 66.52)hsa-miR-548an 2.584625029 2.495584535 1.063662528 0.889373 0.99683407661.22 (43.53, 78.92) hsa-miR-302e 1.654697787 1.728142919 1.0522263850.891141 0.996834076 58.28 (39.81, 76.74) hsa-miR-29b-3p 7.9017721068.004615995 1.073888262 0.894647 0.996834076 59.41 (41.41, 77.41)hsa-miR-1909-3p 1.735070659 1.800146253 1.046139754 0.896469 0.99683407659.64 (40.99, 78.28) hsa-miR-144-3p 11.12536058 11.04642075 1.0562415710.89941 0.996834076 49.89 (31.69, 68.08) hsa-miR-483-3p 3.0749290732.980551599 1.067604635 0.90534 0.996834076 57.82 (39.86, 75.78)hsa-miR-1283 2.755860662 2.6587311 1.069643143 0.91552 0.996834076 57.37(39.2, 75.54) hsa-miR-2116-5p 3.938884341 3.849961376 1.063575880.924722 0.996834076 43.76 (25.66, 61.87) hsa-miR-644a 3.4354976283.348938191 1.061834879 0.926184 0.996834076 61.9 (43.95, 79.86)hsa-miR-16-5p 13.39920769 13.35316208 1.032431176 0.928528 0.99683407654.65 (36.25, 73.05) hsa-miR-1286 2.353067246 2.39897386 1.032331710.930227 0.996834076 56.92 (38.1, 75.74) hsa-miR-20a-5p + 10.3369863510.37678015 1.027966891 0.930243 0.996834076 46.94 (28.91, 64.97)hsa-miR-20b-5p hsa-miR-548z 4.023611603 4.104783787 1.057877213 0.9302610.996834076 44.67 (26.52, 62.82) hsa-miR-4516 5.255182651 5.2065619571.03427562 0.93686 0.996834076 50.11 (31.92, 68.31) hsa-miR-15b-5p11.25727487 11.21434518 1.030203744 0.938165 0.996834076 54.42 (36.33,72.51) hsa-miR-95 1.57943031 1.614876557 1.024873783 0.9399580.996834076 58.96 (40.81, 77.1) hsa-miR-548aj-3p 2.454456398 2.4967234651.029730686 0.945902 0.996834076 54.88 (36.55, 73.2) hsa-miR-1225-5p1.805566379 1.774806251 1.021550219 0.949197 0.996834076 59.18 (40.78,77.58) hsa-miR-421 2.126777928 2.159630406 1.023032854 0.9493460.996834076 56.92 (38.6, 75.23) hsa-miR-330-5p 1.7563051 1.7316749931.017218853 0.961125 0.996834076 60.09 (42, 78.18) hsa-miR-1260b3.300520497 3.262513356 1.026694628 0.966503 0.996834076 57.6 (39.39,75.8) hsa-let-7g-5p 11.95697546 11.94017645 1.011712242 0.9701120.996834076 52.61 (34.52, 70.7) hsa-miR-647 1.695577265 1.6776529281.012501705 0.970807 0.996834076 55.56 (37.54, 73.57) hsa-miR-548al7.515115326 7.483156786 1.022399149 0.971989 0.996834076 60.54 (42.44,78.65) hsa-miR-518c-3p 1.811948853 1.795002991 1.011815231 0.9727130.996834076 57.14 (38.82, 75.46) hsa-miR-520h 2.89411999 2.8746063571.013617707 0.97275 0.996834076 47.62 (29.32, 65.92) hsa-let-7b-5p10.99090937 11.00523262 1.009977569 0.973133 0.996834076 51.7 (33.39,70.01) hsa-let-7i-5p 8.797476785 8.781816025 1.010914344 0.9797880.996834076 58.05 (39.65, 76.45) hsa-miR-614 1.881240144 1.8713654651.006868084 0.980362 0.996834076 59.64 (41.77, 77.5) hsa-miR-45082.944305798 2.9611139 1.01171862 0.981551 0.996834076 49.89 (31.79,67.98) hsa-miR-22-3p 10.06059719 10.05543513 1.003584475 0.989070.996834076 53.06 (35.03, 71.09) hsa-miR-3934 2.386905365 2.3816275841.003664979 0.991045 0.996834076 60.77 (42.29, 79.26) hsa-miR-150-5p8.975382521 8.978884461 1.002430308 0.995193 0.996834076 53.97 (36.02,71.92) hsa-let-7c 3.271043481 3.267934067 1.002157606 0.9963410.996834076 44.44 (25.83, 63.06) hsa-miR-876-3p 1.950449012 1.9482214181.001545243 0.996834 0.996834076 57.14 (38.78, 75.51)

D. IPMN Tumors Tissue and Paired Plasma have Distinct miRNA ExpressionProfiles

To address whether circulating miRNA expression reflects miRNAexpression in corresponding IPMN tumor tissue, we evaluated matchedplasma and tissue specimens from 12 IPMN cases. Of a total of 160 miRNAprobes that were evaluated in both specimen types, expression levels ofonly 3 (1.9%) were significantly positively correlated (r>0.60, p<0.05)in matched tissue and plasma, and included miR-484 (r=0.70, p=0.015),miR-330 (r=0.63, p=0.026), and miR-574-3p (r=0.64, p=0.030) (Table 10).Of these three miRNA probes, one (miR-574-3p) was represented in the5-miRNA signature that differentiated between malignant and benignIPMNs. For the miRNAs that were ranked as the most highly expressed inthe plasma of IPMN cases versus controls (i.e., miR-146a-5p, miR-340-5p,and miR-181a-5p), correlations with tissue miRNA expression were small(r<0.60) (Table 10). Overall, our data suggest plasma and tissue samplesfrom patients with IPMNs can have distinct miRNA expression profiles.

TABLE 10 Correlation between Paired Tissue and Plasma MiRNA Expressionin 12 Individuals with IPMNs Spearman IPMN vs Control Malignant vsBenign Tissue MiRNA Probe Plasma MiRNA Probe Correlation P Value 30miRNA Signature 5 miRNA Signature hsa-miR-876-5p-002205 (FAM, NFQ)hsa-miR-876-3p −0.75267378 0.004727878 hsa-miR-219-000522 (FAM, NFQ)hsa-miR-219-5p −0.740561791 0.005872143 hsa-miR-484-001821 (FAM, NFQ)hsa-miR-484 0.699300699 0.014539312 hsa-miR-219-000522 (FAM, NFQ)hsa-miR-219-1-3p −0.657352601 0.020182953 hsa-miR-330-000544 (FAM, NFQ)hsa-miR-330-5p 0.633818534 0.026890701 hsa-miR-574-3p-002349 (FAM, NFQ)hsa-miR-574-3p 0.636363636 0.030114265 Yes hsa-miR-34c-000428 (FAM, NFQ)hsa-miR-34c-5p 0.565925895 0.055108369 hsa-miR-338-3p-002252 (FAM, NFQ)hsa-miR-338-3p 0.542266968 0.068541125 hsa-miR-361-000554 (FAM, NFQ)hsa-miR-361-3p −0.545454545 0.070678905 hsa-miR-375-000564 (FAM, NFQ)hsa-miR-375 −0.545454545 0.070678905 hsa-miR-136-000592 (FAM, NFQ)hsa-miR-136-5p −0.533892354 0.073792459 hsa-miR-324-3p-002161 (FAM, NFQ)hsa-miR-324-5p 0.531468531 0.079302939 hsa-miR-330-5p-002230 (FAM, NFQ)hsa-miR-330-5p −0.514021118 0.087341289 hsa-miR-548d-5p-002237 (FAM,NFQ) hsa-miR-548d-3p −0.507054827 0.092464184 hsa-miR-579-002398 (FAM,NFQ) hsa-miR-579 0.51048951 0.09360538 hsa-miR-223-002295 (FAM, NFQ)hsa-miR-223-3p 0.496503497 0.104092833 yes hsa-miR-197-000497 (FAM, NFQ)hsa-miR-197-3p 0.496503497 0.104092833 hsa-miR-21-000397 (FAM, NFQ)hsa-miR-21-5p 0.482517483 0.115373605 hsa-miR-431-001979 (FAM, NFQ)hsa-miR-431-5p −0.468126376 0.124825063 hsa-miR-188-3p-002106 (FAM, NFQ)hsa-miR-188-5p −0.465971464 0.126806857 hsa-miR-125a-5p-002198 (FAM,NFQ) hsa-miR-125a-5p 0.461538462 0.133836316 hsa-miR-155-002623 (FAM,NFQ) hsa-miR-155-5p −0.461538462 0.133836316 hsa-miR-98-000577 (FAM,NFQ) hsa-miR-98 0.41604595 0.178556865 yes hsa-miR-423-5p-002340 (FAM,NFQ) hsa-miR-423-5p 0.412587413 0.184480685 yes hsa-miR-148a-000470(FAM, NFQ) hsa-miR-148a-3p 0.405594406 0.192612184 yeshsa-miR-548d-001605 (FAM, NFQ) hsa-miR-548d-3p 0.399404112 0.198348249hsa-miR-342-3p-002260 (FAM, NFQ) hsa-miR-342-3p −0.391608392 0.209564352hsa-miR-660-001515 (FAM, NFQ) hsa-miR-660-5p 0.391608392 0.209564352hsa-miR-888-002212 (FAM, NFQ) hsa-miR-888-5p −0.387333548 0.213511553hsa-miR-142-5p-002248 (FAM, NFQ) hsa-miR-142-3p −0.377622378 0.227443132hsa-miR-152-000475 (FAM, NFQ) hsa-miR-152 0.370629371 0.236732214hsa-miR-216b-002326 (FAM, NFQ) hsa-miR-216b −0.365768413 0.242300452hsa-miR-454-002323 (FAM, NFQ) hsa-miR-454-3p −0.356643357 0.256012537hsa-miR-23a-000399 (FAM, NFQ) hsa-miR-23a-3p 0.348054616 0.267575666 yeshsa-let-7e-002406 (FAM, NFQ) hsa-let-7e-5p 0.342657343 0.276230513hsa-miR-367-000555 (FAM, NFQ) hsa-miR-367-3p −0.336252705 0.285226087hsa-miR-192-000491 (FAM, NFQ) hsa-miR-192-5p 0.335664336 0.286690914hsa-miR-10a-000387 (FAM, NFQ) hsa-miR-10a-5p −0.335664336 0.286690914hsa-miR-125a-3p-002199 (FAM, NFQ) hsa-miR-125a-5p 0.3222421750.307014179 hsa-miR-107-000443 (FAM, NFQ) hsa-miR-107 0.3216783220.308312361 yes hsa-miR-24-000402 (FAM, NFQ) hsa-miR-24-3p 0.3216783220.308312361 yes hsa-miR-483-5p-002338 (FAM, NFQ) hsa-miR-483-3p−0.321678322 0.308312361 hsa-let-7a-000377 (FAM, NFQ) hsa-let-7a-5p0.314685315 0.319471913 yes hsa-miR-891a-002191 (FAM, NFQ) hsa-miR-891a0.3117829 0.323864452 hsa-miR-489-002358 (FAM, NFQ) hsa-miR-4890.311734278 0.323943941 hsa-miR-325-000540 (FAM, NFQ) hsa-miR-325−0.305699203 0.333893136 hsa-miR-450b-3p-002208 (FAM, NFQ)hsa-miR-450b-5p −0.305699203 0.333893136 hsa-miR-219-2-3p-002390 (FAM,NFQ) hsa-miR-219-5p −0.305699203 0.333893136 hsa-miR-516a-5p-002416(FAM, NFQ) hsa-miR-516a-5p −0.305699203 0.333893136 hsa-miR-133b-002247(FAM, NFQ) hsa-miR-133b −0.275368456 0.386340424 mmu-miR-93-001090 (FAM,NFQ) hsa-miR-93-5p 0.26970269 0.396580033 hsa-miR-127-5p-002229 (FAM,NFQ) hsa-miR-127-3p −0.266269408 0.402851144 hsa-miR-185-002271 (FAM,NFQ) hsa-miR-185-5p 0.265734266 0.403976659 hsa-miR-106b-000442 (FAM,NFQ) hsa-miR-106b-5p 0.258741259 0.416938427 hsa-miR-26b-000407 (FAM,NFQ) hsa-miR-26b-5p 0.258741259 0.416938427 hsa-let-7c-000379 (FAM, NFQ)hsa-let-7c −0.258741259 0.416938427 hsa-miR-382-000572 (FAM, NFQ)hsa-miR-382-5p 0.257333899 0.419403871 hsa-miR-146a-000468 (FAM, NFQ)hsa-miR-146a-5p −0.251748252 0.430115289 yes hsa-let-7f-000382 (FAM,NFQ) hsa-let-7f-5p 0.237762238 0.457102207 yes hsa-miR-199a-000498 (FAM,NFQ) hsa-miR-199a-5p −0.237762238 0.457102207 hsa-miR-199a-3p-002304(FAM, NFQ) hsa-miR-199a-5p −0.237762238 0.457102207 hsa-miR-150-000473(FAM, NFQ) hsa-miR-150-5p 0.237762238 0.457102207 hsa-miR-143-002249(FAM, NFQ) hsa-miR-143-3p −0.237762238 0.457102207 hsa-miR-212-000515(FAM, NFQ) hsa-miR-212-3p −0.237762238 0.457102207 hsa-miR-518b-001156(FAM, NFQ) hsa-miR-518b −0.233939909 0.464282613 hsa-miR-590-5p-001984(FAM, NFQ) hsa-miR-590-5p 0.230769231 0.470905694 hsa-miR-186-002285(FAM, NFQ) hsa-miR-186-5p −0.230769231 0.470905694 hsa-miR-99b-000436(FAM, NFQ) hsa-miR-99b-5p 0.230769231 0.470905694 hsa-let-7d-002283(FAM, NFQ) hsa-let-7d-5p 0.223776224 0.48491114 yeshsa-miR-219-2-3p-002390 (FAM, NFQ) hsa-miR-219-1-3p −0.2183565730.49536676 hsa-miR-450b-5p-002207 (FAM, NFQ) hsa-miR-450b-5p−0.218356573 0.49536676 hsa-miR-181a-000480 (FAM, NFQ) hsa-miR-181a-5p−0.216783217 0.499114748 yes hsa-miR-335-000546 (FAM, NFQ)hsa-miR-335-5p 0.216783217 0.499114748 yes hsa-miR-425-5p-001516 (FAM,NFQ) hsa-miR-425-5p −0.213660573 0.504912688 hsa-miR-191-002299 (FAM,NFQ) hsa-miR-191-5p 0.20979021 0.513512513 yes hsa-miR-324-5p-000539(FAM, NFQ) hsa-miR-324-5p 0.20979021 0.513512513 hsa-miR-127-000452(FAM, NFQ) hsa-miR-127-3p −0.20979021 0.513512513 hsa-miR-654-3p-002239(FAM, NFQ) hsa-miR-654-3p 0.208022975 0.516479059 hsa-miR-331-000545(FAM, NFQ) hsa-miR-331-3p −0.204230416 0.524324327 hsa-miR-221-000524(FAM, NFQ) hsa-miR-221-3p 0.192644779 0.548602519 hsa-miR-29c-000587(FAM, NFQ) hsa-miR-29c-3p 0.188811189 0.557827775 yes hsa-miR-16-000391(FAM, NFQ) hsa-miR-16-5p 0.188811189 0.557827775 hsa-miR-423-5p-002340(FAM, NFQ) hsa-miR-423-3p 0.181818182 0.572958221 hsa-miR-487b-001285(FAM, NFQ) hsa-miR-487b 0.176060704 0.58414053 hsa-miR-302b-000531 (FAM,NFQ) hsa-miR-302b-3p 0.176060704 0.58414053 hsa-miR-32-002109 (FAM, NFQ)hsa-miR-32-5p −0.174825175 0.588259895 hsa-miR-130a-000454 (FAM, NFQ)hsa-miR-130a-3p 0.167832168 0.603727651 hsa-miR-570-002347 (FAM, NFQ)hsa-miR-570-3p −0.166642584 0.604712895 hsa-miR-515-3p-002369 (FAM, NFQ)hsa-miR-515-5p −0.165221074 0.607841489 hsa-miR-23b-000400 (FAM, NFQ)hsa-miR-23b-3p 0.160839161 0.619356169 hsa-miR-652-002352 (FAM, NFQ)hsa-miR-652-3p 0.160839161 0.619356169 hsa-miR-30b-000602 (FAM, NFQ)hsa-miR-30b-5p 0.153846154 0.635139955 yes hsa-miR-200a-000502 (FAM,NFQ) hsa-miR-200a-3p 0.153846154 0.635139955 Yes hsa-miR-363-001271(FAM, NFQ) hsa-miR-363-3p 0.146853147 0.651073351hsa-miR-219-1-3p-002095 (FAM, NFQ) hsa-miR-219-1-3p 0.1451403150.652662819 hsa-miR-340-002258 (FAM, NFQ) hsa-miR-340-5p 0.139860140.667150536 yes hsa-miR-25-000403 (FAM, NFQ) hsa-miR-25-3p 0.139860140.667150536 hsa-miR-486-3p-002093 (FAM, NFQ) hsa-miR-486-3p −0.135252730.675137513 hsa-miR-126-002228 (FAM, NFQ) hsa-miR-126-3p 0.1328671330.683365534 yes mmu-miR-140-001187 (FAM, NFQ) hsa-miR-140-5p−0.132867133 0.683365534 hsa-miR-487a-001279 (FAM, NFQ) hsa-miR-487a0.131013944 0.684848714 hsa-miR-520f-001120 (FAM, NFQ) hsa-miR-520f−0.131013944 0.684848714 hsa-miR-18a-002422 (FAM, NFQ) hsa-miR-18a-5p−0.125874126 0.699712221 yes hsa-let-7b-002619 (FAM, NFQ) hsa-let-7b-5p0.125874126 0.699712221 hsa-miR-222-002276 (FAM, NFQ) hsa-miR-222-3p−0.125874126 0.699712221 hsa-miR-141-000463 (FAM, NFQ) hsa-miR-141-3p−0.125874126 0.699712221 hsa-miR-494-002365 (FAM, NFQ) hsa-miR-4940.123269343 0.702704573 hsa-miR-145-002278 (FAM, NFQ) hsa-miR-145-5p−0.1210156 0.707927241 yes hsa-miR-92a-000431 (FAM, NFQ) hsa-miR-92a-3p−0.118881119 0.716184327 hsa-miR-219-1-3p-002095 (FAM, NFQ)hsa-miR-219-5p 0.112886912 0.726858861 hsa-miR-27a-000408 (FAM, NFQ)hsa-miR-27a-3p 0.111888112 0.732775446 yes hsa-miR-29b-000413 (FAM, NFQ)hsa-miR-29b-3p 0.111888112 0.732775446 hsa-miR-376c-002122 (FAM, NFQ)hsa-miR-376c 0.111888112 0.732775446 hsa-miR-548a-001538 (FAM, NFQ)hsa-miR-548a-3p −0.109171957 0.735558555 hsa-miR-142-3p-000464 (FAM,NFQ) hsa-miR-142-3p −0.10507897 0.745176622 yes hsa-miR-15b-000390 (FAM,NFQ) hsa-miR-15b-5p 0.104895105 0.749479043 yes hsa-miR-95-000433 (FAM,NFQ) hsa-miR-95 0.104895105 0.749479043 hsa-miR-125b-000449 (FAM, NFQ)hsa-miR-125b-5p 0.090909091 0.78319691 hsa-miR-28-000411 (FAM, NFQ)hsa-miR-28-3p −0.083916084 0.800197518 hsa-miR-149-002255 (FAM, NFQ)hsa-miR-149-5p −0.079762516 0.80536501 hsa-miR-140-3p-002234 (FAM, NFQ)hsa-miR-140-5p 0.076923077 0.817283291 hsa-let-7g-002282 (FAM, NFQ)hsa-let-7g-5p 0.06993007 0.834447145 yes hsa-miR-28-3p-002446 (FAM, NFQ)hsa-miR-28-5p −0.06993007 0.834447145 hsa-miR-410-001274 (FAM, NFQ)hsa-miR-410 −0.06993007 0.834447145 hsa-miR-19b-000396 (FAM, NFQ)hsa-miR-19b-3p 0.066550014 0.837187854 hsa-miR-486-001278 (FAM, NFQ)hsa-miR-486-3p 0.062937063 0.851681911 hsa-miR-574-3p-002349 (FAM, NFQ)hsa-miR-574-5p −0.062937063 0.851681911 hsa-miR-627-001560 (FAM, NFQ)hsa-miR-627 −0.055984961 0.862798664 hsa-miR-450a-002303 (FAM, NFQ)hsa-miR-450a-5p 0.055073691 0.865013709 hsa-miR-28-3p-002446 (FAM, NFQ)hsa-miR-28-3p −0.055944056 0.868980339 hsa-miR-376a-000565 (FAM, NFQ)hsa-miR-376a-3p 0.055944056 0.868980339 hsa-miR-485-3p-001277 (FAM, NFQ)hsa-miR-485-3p 0.055944056 0.868980339 hsa-miR-409-5p-002331 (FAM, NFQ)hsa-miR-409-3p −0.043671315 0.892800448 hsa-miR-29a-002112 (FAM, NFQ)hsa-miR-29a-3p −0.041958042 0.903738836 hsa-miR-15a-000389 (FAM, NFQ)hsa-miR-15a-5p −0.034965035 0.921184083 hsa-miR-19a-000395 (FAM, NFQ)hsa-miR-19a-3p −0.034965035 0.921184083 hsa-miR-122-002245 (FAM, NFQ)hsa-miR-122-5p −0.029123216 0.928410573 mmu-miR-495-001663 (FAM, NFQ)hsa-miR-495 0.028169713 0.930749393 hsa-miR-337-5p-002156 (FAM, NFQ)hsa-miR-337-3p 0.028169713 0.930749393 hsa-miR-370-002275 (FAM, NFQ)hsa-miR-370 −0.020802297 0.948836372 hsa-miR-26a-000405 (FAM, NFQ)hsa-miR-26a-5p 0.020979021 0.956169155 yes hsa-miR-361-000554 (FAM, NFQ)hsa-miR-361-5p 0.020979021 0.956169155 hsa-miR-28-000411 (FAM, NFQ)hsa-miR-28-5p −0.020979021 0.956169155 hsa-miR-598-001988 (FAM, NFQ)hsa-miR-598 0.020979021 0.956169155 hsa-miR-22-000398 (FAM, NFQ)hsa-miR-22-3p −0.017513162 0.956918824 yes hsa-miR-515-5p-001112 (FAM,NFQ) hsa-miR-515-5p −0.016126702 0.960326954 hsa-miR-331-5p-002233 (FAM,NFQ) hsa-miR-331-3p −0.013986014 0.973693904 hsa-miR-337-5p-002156 (FAM,NFQ) hsa-miR-337-5p 0 1 yes hsa-miR-27b-000409 (FAM, NFQ) hsa-miR-27b-3p0 1 hsa-miR-148b-000471 (FAM, NFQ) hsa-miR-148b-3p 0 1hsa-miR-503-001048 (FAM, NFQ) hsa-miR-503 NA NA hsa-miR-891b-002210(FAM, NFQ) hsa-miR-891b NA NA hsa-miR-518c-002401 (FAM, NFQ)hsa-miR-518c-3p NA NA hsa-miR-342-5p-002147 (FAM, NFQ) hsa-miR-342-3p NANA hsa-miR-654-001611 (FAM, NFQ) hsa-miR-654-3p NA NAhsa-miR-548a-5p-002412 (FAM, NFQ) hsa-miR-548a-3p NA NAhsa-miR-876-3p-002225 (FAM, NFQ) hsa-miR-876-3p NA NAhsa-miR-485-5p-001036 (FAM, NFQ) hsa-miR-485-3p NA NA hsa-miR-384-000574(FAM, NFQ) hsa-miR-384 NA NA hsa-miR-448-001029 (FAM, NFQ) hsa-miR-448NA NA

This is the first report to interrogate plasma miRNA expression levelsexclusively in individuals newly-diagnosed with IPMNs and healthycontrols. We used highly sensitive and specific NCOUNTER™ technology formiRNA quantitation and implemented an extensive quality control and dataanalysis pipeline to account for pre-analytical and technical factorsthat can affect circulating miRNA levels and result in biases that donot reflect the underlying biology of the samples. This studydemonstrates the feasibility of evaluating plasma miRNAs using NCOUNTER™technology, and our results suggest that miRNAs circulating in plasmawarrant further evaluation as minimally invasive biomarkers for thedetection of PDAC precursors and as possible targets for chemopreventionefforts.

We show that a 30-miRNA gene signature can discriminate IPMN cases fromnon-diseased healthy controls ((AUC)=74.4 (95% CI:62.3-86.5, p=0.002)).Fortunately, a number of the miRNAs highlighted in this signature(let-7a-5p, let-7d-5p, miR-1260b, miR-142-3p, and miR-146a-5p,miR-23a-3p) have been shown to be unaffected by hemolysis (63,65), whichminimizes red blood cell contamination as a potential source ofconfounding. The miRNAs represented in the signature had 2-4-fold higherexpression in cases compared to controls, and included miRNAs previouslyshown to be up-regulated in PDAC versus normal tissues (i.e., miR-107,miR-145, miR-146a, miR-15b, miR-181a, and miR-24) (75) and miRNAs shownto be down-regulated in PDAC versus normal tissues (i.e., miR-142,miR-148a) (75). Noteworthy, several identified miRNAs (miR-145-5p andmiR-335) may be involved in inhibiting cancer stem cell properties ofpancreatic cancers by targeting the transcription factor, OCT4 (76,77).Candidate miRNAs such as miR-1260b and miR-4454 are novel and also ofinterest because validated targets include key players in pancreaticcarcinogenesis, SMAD4 (78) and NF-κβ (79), respectively. Collectively,the biological plausibility of findings was enhanced by in silicopathway-based exploratory analysis which predicted that the 30differentially expressed circulating miRNAs may affect critical pathwaysinvolved in PDAC initiation and progression.

Li et al. (48) recently reported on their efforts to identify miRNAlevels in sera that could distinguish patients with early-stage PDACfrom healthy controls. miR-1290 had the best diagnostic performance forsubjects with PDAC (n=41) relative to healthy controls (n=19), and serummiR-1290 levels were also significantly higher than controls among 20patients with IPMNs (AUC=0.76). Although miR-1290 was evaluated as partof the NCOUNTER miRNA codeset, expression levels of this miRNA were notanalyzed because 93% of the 69 samples had values below backgroundlevels. Two miRNAs from our 30-miRNA gene signature, miR-24 andmiR-146a, were among the miRNAs that distinguished sera of patients withPDAC from healthy controls with AUCs>0.70 in the study by Li et al.(48), but comparisons of these levels in IPMNs versus healthy controlswere not reported. None of the circulating miRNAs identified in ourstudy overlapped with three miRNAs (miR-642b, miR-885,5-p, miR-22)highlighted in a small study of plasma miRNA expression in early PDACpatients versus controls by Ganepola and colleagues (58).

We also conducted exploratory analysis and discovered a 5-miRNAsignature (comprising miR-200a-3p, miR-1185-5p, miR-33a-5p, miR-574-3p,and miR-663b) that can discriminate between malignant and benign IPMNs(AUC=73.2 (95% CI: 57.6-88.9)). These miRNAs had 2-3 fold lowerexpression in the plasma of malignant as opposed to benign cases.Consistent with our findings of reduced miR-200a expression in malignantIPMNs, miR-200a down-regulation has been implicated inepithelial-to-mesenchymal transition and early metastasis (75). On theother hand, miR-200a was previously shown to be hypomethylated andoverexpressed in PDAC (compared to normal) tissue and in the sera ofPDAC patients versus controls (80). Another miRNA in the signature,miR-574-3p, has been shown to act as a tumor suppressor and to regulatecell signaling pathways in prostate and gastric cancer cells (81,82),suggesting low levels of miR-574-3p may regulate key oncogenes thatpromote malignant IPMN status. Although the identified circulatingmiRNAs may play a role in differentiating between malignant and benignIPMNs, larger studies that account for clinical and radiologic factorsare needed to confirm and expand upon these findings.

Based on our observation that candidate plasma miRNA levels were notstrongly correlated with paired tissue miRNA expression in a subset ofIPMN cases, it will also be necessary to further explore the origin ofcirculating miRNAs in IPMN patients. Discrepancies between plasma andtumor miRNA profiles have been reported previously (72,83), challengingthe popular hypothesis that the origin of circulating miRNAs is fromtumors as a result of cell death and lysis. Alternative explanations forthe origin of circulating miRNAs include the following: blood cellcontamination; normal cell contamination; tumor cells release miRNAsinto the tumor microenvironment where they enter newly formed bloodvessels and make their way into circulation; heterogeneity of theprimary tumor; dietary sources; and locoregional inflammation thatreflects a systematic response of the host microenvironment to thedisease (64,84-86). It is also possible that certain miRNA sequencescould be more easily degraded and/or or more easily released from cells,affecting differential expression. Taken together, this data suggeststhat biomarker discovery of circulating miRNAs seems to warrant agenome-wide approach rather than relying on differentially expressedmiRNAs identified through tissue-based studies.

With archived plasma available from a total of 42 cases and 24 controlswe had at least 85% power to detect a miRNA expression difference of2-fold and above, assuming a set of 800 miRNAs, a standard deviation of1, and a 15% FDR. Technical validation of the Nanostring assay andexternal validation of findings in a large, independent study populationmay be done. Further, a large-scale prospective investigation of serialplasma miRNA measurements (pre- and post-surgery or during surveillance)may be done for individuals newly-diagnosed with various types ofpancreatic cysts (including IPMNs, MCNs, and benign, non-mucinous cysts)and early-stage PDAC and those at high genetic risk for developing PDAC.To increase diagnostic accuracy and improve outcomes, it will also benecessary to integrate novel classes of molecular markers and/or imagingtechniques to improve sensitivity and specificity of the miRNA-basedassay in conjunction with clinical characteristics.

In summary, our methodologically-sound study is the first of its kind tosupport the development of a plasma miRNA assay to detect IPMNs usingNCOUNTER™ technology. Future large-scale studies with rigorous designsare needed to further explore the exciting potential for circulatingmiRNAs to be utilized clinically as novel biomarkers for IPMNs andpossibly other PDAC precursors.

It should be understood that the examples and embodiments describedherein are for illustrative purposes only and that various modificationsor changes in light thereof will be suggested to persons skilled in theart and are to be included within the spirit and purview of thisapplication and the scope of the appended claims. In addition, anyelements or limitations of any invention or embodiment thereof disclosedherein can be combined with any and/or all other elements or limitations(individually or in any combination) or any other invention orembodiment thereof disclosed herein, and all such combinations arecontemplated with the scope of the invention without limitation thereto.

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We claim:
 1. A method of treating and/or preventing the development ofpancreatic cancer in a subject, the method comprising: (a) detecting thelevel of expression of one or more miRNAs in a sample from the subject;(b) comparing the detected expression level to a reference expressionlevel, wherein a differential expression of the one or more miRNAs inthe sample, as compared to the reference expression level, is indicativeof the presence of pancreatic cancer, or a higher risk of developingpancreatic cancer, versus the absence of pancreatic cancer, or a lowerrisk of developing pancreatic cancer, respectively; and (c)administering a therapy to treat and/or prevent the pancreatic cancer tothe subject identified as having the pancreatic cancer, or at a higherrisk of developing pancreatic cancer.
 2. The method of claim 1, whereina differential expression of the one or more miRNAs in the sample, ascompared to the reference expression level, is indicative of apancreatic cancer precursor (such as intraductal papillary mucinousneoplasm (IPMN)) versus non-IPMN (normal cells).
 3. The method of claim1, wherein the one or more miRNAs are selected from miR-100, miR-99b,miR-99a, miR-342-3p, miR-126, miR-888, miR-130a, let-7c, miR-150,miR-296, miR-199a, miR-199a-3p, and miR-302a.
 4. The method of claim 1,wherein the one or more mRNAs are selected from among let-7a-5p,let-7d-5p, let-7f-5p, let-7g-5p, let-7i-5p, miR-107, miR-1260b,miR-126-3p, miR-142-3p, miR-145-5p, miR-146a-5p, miR-148a-3p,miR-15b-5p, miR-181a-5p, miR-191-5p, miR-199a-3p, miR-199b-3p,miR-20a-5p, miR-20b-5p, miR-22-3p, miR-23a-3p, miR-24-3p, miR-26a-5p,miR-27a-3p, miR-29c-3p, miR-335-5p, miR-337-5p, miR-340-5p, miR-423-5p,miR-4454, miR-593-3p, and miR-98.
 5. The method of claim 1, wherein theone or more mRNAs are selected from among miR-200a-3p, miR-1185-5p,miR-33a-5p, miR-574-3p, and miR-663b.
 6. A method of treating and/orpreventing pancreatic cancer in a subject, comprising measuring thelevel of expression of one or more miRNAs in a sample obtained from thesubject; and administering a treatment for the pancreatic cancer,wherein the one or more miRNAs comprise: (a) one or more mRNAs selectedfrom among miR-100, miR-99b, miR-99a, miR-342-3p, miR-126, miR-888,miR-130a, let-7c, miR-150, miR-296, miR-199a, miR-199a-3p, and miR-302a;or (b) one or more mRNAs selected from among let-7a-5p, let-7d-5p,let-7f-5p, let-7g-5p, let-7i-5p, miR-107, miR-1260b, miR-126-3p,miR-142-3p, miR-145-5p, miR-146a-5p, miR-148a-3p, miR-15b-5p,miR-181a-5p, miR-191-5p, miR-199a-3p, miR-199b-3p, miR-20a-5p,miR-20b-5p, miR-22-3p, miR-23a-3p, miR-24-3p, miR-26a-5p, miR-27a-3p,miR-29c-3p, miR-335-5p, miR-337-5p, miR-340-5p, miR-423-5p, miR-4454,miR-593-3p, and miR-98; or (c) one or more mRNAs selected from amongmiR-200a-3p, miR-1185-5p, miR-33a-5p, miR-574-3p, and miR-663b.
 7. Themethod of claim 6, wherein the one or more miRNAs comprise one or morefrom among miR-1185-5p, miR-33a-5p, miR-574-3p, and miR-663b.
 8. Acomposition of matter comprising: (a) a microarray chip corresponding toa profile of miRNAs that are differentially expressed in a sample of anindividual having pancreatic cancer, or having a high risk of developingpancreatic cancer, as compared to the corresponding sample of anindividual having no risk or low risk of developing pancreatic cancer,the microarray chip consisting essentially of oligonucleotidescorresponding to one or more of miRNA selected from among miR-100,miR-99b, miR-99a, miR-342-3p, miR-126, miR-888, miR-130a, let-7c,miR-150, miR-296, miR-199a, miR-199a-3p, and miR-302a; or (b) amicroarray chip corresponding to a profile of miRNAs that aredifferentially expressed in a sample of an individual having apancreatic lesion and having high risk of developing pancreatic cancercompared to the corresponding sample of an individual having thepancreatic lesion and having no risk or low risk of developingpancreatic cancer, the microarray chip consisting essentially ofoligonucleotides corresponding to one or more selected from amongmiR-100, miR-99b, miR-99a, miR-342-3p, miR-126, miR-888, miR-130a,let-7c, miR-150, miR-296, miR-199a, miR-199a-3p, and miR-302a; or (c) amicroarray chip corresponding to a profile of miRNAs that aredifferentially expressed in a sample of an individual having apancreatic cancer precursor (such as intraductal papillary mucinousneoplasm (IPMN)) as compared to a non-IPMN (normal cells), themicroarray chip consisting essentially of oligonucleotides correspondingto one or more of miRNA selected from among one or more miRNA selectedfrom among let-7a-5p, let-7d-5p, let-7f-5p, let-7g-5p, let-7i-5p,miR-107, miR-1260b, miR-126-3p, miR-142-3p, miR-145-5p, miR-146a-5p,miR-148a-3p, miR-15b-5p, miR-181a-5p, miR-191-5p, miR-199a-3p,miR-199b-3p, miR-20a-5p, miR-20b-5p, miR-22-3p, miR-23a-3p, miR-24-3p,miR-26a-5p, miR-27a-3p, miR-29c-3p, miR-335-5p, miR-337-5p, miR-340-5p,miR-423-5p, miR-4454, miR-593-3p, and miR-98; or (d) a microarray chipcorresponding to a profile of miRNAs that are differentially expressedin a sample of an individual having a malignant intraductal papillarymucinous neoplasm (IPMN)) as compared to a benign IPMN, the microarraychip consisting essentially of oligonucleotides corresponding to one ormore of miRNA selected from among one or more miRNA selected from amongmiR-200a-3p, miR-1185-5p, miR-33a-5p, miR-574-3p, and miR-663b.